Mercurial > repos > rnateam > graphprot_predict_profile
changeset 1:20429f4c1b95 draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/rna_tools/graphprot commit f3fb925b83a4982e0cf9a0c11ff93ecbb8e4e6d5"
| author | bgruening |
|---|---|
| date | Wed, 22 Jan 2020 10:14:41 -0500 |
| parents | 215925e588c4 |
| children | 7bbb7bf6304f |
| files | data/EWSR1_eCLIP_K562_ENCSR887LPK.tar.gz data/FMR1_eCLIP_K562_ENCSR331VNX.tar.gz data/HNRNPC_eCLIP_HepG2_ENCSR550DVK.tar.gz data/HUR_PAR-CLIP_HEK293_Mukherjee.tar.gz data/IGF2BP1-3_PAR-CLIP_HEK293_Hafner.tar.gz data/IGF2BP1-3_PAR-CLIP_HEK293_Hafner_structure.tar.gz data/KHDRBS1_eCLIP_K562_ENCSR628IDK.tar.gz data/KHDRBS1_eCLIP_K562_ENCSR628IDK_structure.tar.gz data/PUM2_PAR-CLIP_HEK293_Hafner.tar.gz data/PUM2_eCLIP_K562_exonized_3utr.tar.gz data/QKI_PAR-CLIP_HEK293_Hafner.tar.gz data/QKI_eCLIP_HepG2_ENCSR570WLM.tar.gz data/QKI_eCLIP_HepG2_ENCSR570WLM_structure.tar.gz gplib.py graphprot_predict_profile.xml graphprot_predict_profile_wrapper.pl graphprot_predict_wrapper.py graphprot_train_predict.xml graphprot_train_wrapper.py test-data/GraphProt_predict_profile_test_out1.average_profile test-data/GraphProt_predict_profile_test_out1.peak_regions.bed test-data/GraphProt_predict_profile_test_out1.peak_regions_p50.bed test-data/GraphProt_predict_profile_test_out2.average_profile test-data/GraphProt_predict_profile_test_out2.peak_regions.bed test-data/GraphProt_predict_profile_test_out3.average_profile test-data/GraphProt_predict_profile_test_out3.peak_regions.bed test-data/GraphProt_predict_profile_test_out4.average_profile test-data/GraphProt_predict_profile_test_out4.peak_regions.bed test-data/GraphProt_predict_profile_test_out4.peak_regions_p50.bed test-data/empty_file test-data/file1 test-data/file2 test-data/structure_test.model test-data/structure_test.params test-data/test.ensembl.fa test-data/test.fa test-data/test.model test-data/test.params test-data/test.peaks.bed test-data/test.peaks_genomic.bed test-data/test.predictions test-data/test.profile test-data/test.sequence_motif test-data/test1.bed test-data/test2.bed test-data/test2.fa test-data/test2.profile test-data/test2_1.avg_profile test-data/test2_2.avg_profile test-data/test2_3.avg_profile test-data/test3.fa test-data/test3_added_ids_exp.avg_profile test-data/test3_added_ids_out.avg_profile test-data/test4.avg_profile test-data/test4.bed test-data/test4_out.peaks.bed test-data/test4_out_exp.peaks.bed test-data/test4_out_exp2.peaks.bed test-data/test_exp.peaks.bed test-data/test_negatives.parop.fa test-data/test_negatives.train.fa test-data/test_out.peaks.bed test-data/test_positives.parop.fa test-data/test_positives.train.fa test-data/test_predict.avg_profile test-data/test_predict.avg_profile.genomic_peaks.bed test-data/test_predict.avg_profile.p50.genomic_peaks.bed test-data/test_predict.avg_profile.p50.peaks.bed test-data/test_predict.avg_profile.peaks.bed test-data/test_predict.bed test-data/test_predict.fa test-data/test_predict.p50.predictions test-data/test_predict.predictions |
| diffstat | 71 files changed, 8679 insertions(+), 19521 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/gplib.py Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,1011 @@ + +from distutils.spawn import find_executable +import subprocess +import statistics +import random +import gzip +import uuid +import sys +import re +import os + +""" + +Run doctests: + +python3 -m doctest gplib.py + + +""" + + +################################################################################ + +def graphprot_predictions_get_median(predictions_file): + """ + Given a GraphProt .predictions file, read in site scores and return + the median value. + + >>> test_file = "test-data/test.predictions" + >>> graphprot_predictions_get_median(test_file) + 0.571673 + + """ + # Site scores list. + sc_list = [] + with open(predictions_file) as f: + for line in f: + cols = line.strip().split("\t") + score = float(cols[2]) + sc_list.append(score) + f.close() + # Return the median. + return statistics.median(sc_list) + + +################################################################################ + +def graphprot_profile_get_top_scores_median(profile_file, + profile_type="profile", + avg_profile_extlr=5): + + """ + Given a GraphProt .profile file, extract for each site (identified by + column 1 ID) the top (= highest) score. Then return the median of these + top scores. + + profile_type can be either "profile" or "avg_profile". + "avg_profile means that the position-wise scores will first get smoothed + out by calculating for each position a new score through taking a + sequence window -avg_profile_extlr to +avg_profile_extlr of the position + and calculate the mean score over this window and assign it to the position. + After that, the maximum score of each site is chosen, and the median over + all maximum scores is returned. + "profile" leaves the position-wise scores as they are, directly extracting + the maximum for each site and then reporting the median. + + >>> test_file = "test-data/test.profile" + >>> graphprot_profile_get_top_scores_median(test_file) + 3.2 + + """ + # Dictionary of lists, with list of scores (value) for each site (key). + lists_dic = {} + with open(profile_file) as f: + for line in f: + cols = line.strip().split("\t") + seq_id = cols[0] + score = float(cols[2]) + if seq_id in lists_dic: + lists_dic[seq_id].append(score) + else: + lists_dic[seq_id] = [] + lists_dic[seq_id].append(score) + f.close() + # For each site, extract maximum and store in new list. + max_list = [] + for seq_id in lists_dic: + if profile_type == "profile": + max_sc = max(lists_dic[seq_id]) + max_list.append(max_sc) + elif profile_type == "avg_profile": + # Convert profile score list to average profile scores list. + aps_list = list_moving_window_average_values(lists_dic[seq_id], + win_extlr=avg_profile_extlr) + max_sc = max(aps_list) + max_list.append(max_sc) + else: + assert 0, "invalid profile_type argument given: \"%s\"" %(profile_type) + # Return the median. + return statistics.median(max_list) + + +################################################################################ + +def list_moving_window_average_values(in_list, + win_extlr=5, + method=1): + """ + Take a list of numeric values, and calculate for each position a new value, + by taking the mean value of the window of positions -win_extlr and + +win_extlr. If full extension is not possible (at list ends), it just + takes what it gets. + Two implementations of the task are given, chose by method=1 or method=2. + + >>> test_list = [2, 3, 5, 8, 4, 3, 7, 1] + >>> list_moving_window_average_values(test_list, win_extlr=2, method=1) + [3.3333333333333335, 4.5, 4.4, 4.6, 5.4, 4.6, 3.75, 3.6666666666666665] + >>> list_moving_window_average_values(test_list, win_extlr=2, method=2) + [3.3333333333333335, 4.5, 4.4, 4.6, 5.4, 4.6, 3.75, 3.6666666666666665] + + """ + l_list = len(in_list) + assert l_list, "Given list is empty" + new_list = [0] * l_list + if win_extlr == 0: + return l_list + if method == 1: + for i in range(l_list): + s = i - win_extlr + e = i + win_extlr + 1 + if s < 0: + s = 0 + if e > l_list: + e = l_list + # Extract portion and assign value to new list. + new_list[i] = statistics.mean(in_list[s:e]) + elif method == 2: + for i in range(l_list): + s = i - win_extlr + e = i + win_extlr + 1 + if s < 0: + s = 0 + if e > l_list: + e = l_list + l = e-s + sc_sum = 0 + for j in range(l): + sc_sum += in_list[s+j] + new_list[i] = sc_sum / l + else: + assert 0, "invalid method ID given (%i)" %(method) + return new_list + + +################################################################################ + +def echo_add_to_file(echo_string, out_file): + """ + Add a string to file, using echo command. + + """ + check_cmd = 'echo "%s" >> %s' % (echo_string, out_file) + output = subprocess.getoutput(check_cmd) + error = False + if output: + error = True + assert error == False, "echo is complaining:\n%s\n%s" %(check_cmd, output) + + +################################################################################ + +def is_tool(name): + """Check whether tool "name" is in PATH.""" + return find_executable(name) is not None + + +################################################################################ + +def count_fasta_headers(fasta_file): + """ + Count number of FASTA headers in fasta_file using grep. + + >>> test_file = "test-data/test.fa" + >>> count_fasta_headers(test_file) + 2 + >>> test_file = "test-data/empty_file" + >>> count_fasta_headers(test_file) + 0 + + """ + check_cmd = 'grep -c ">" ' + fasta_file + output = subprocess.getoutput(check_cmd) + row_count = int(output.strip()) + return row_count + + +################################################################################ + +def make_file_copy(in_file, out_file): + """ + Make a file copy by copying in_file to out_file. + + """ + check_cmd = "cat " + in_file + " > " + out_file + assert in_file != out_file, "cat does not like to cat file into same file (%s)" %(check_cmd) + output = subprocess.getoutput(check_cmd) + error = False + if output: + error = True + assert error == False, "cat did not like your input (in_file: %s, out_file: %s):\n%s" %(in_file, out_file, output) + + +################################################################################ + +def split_fasta_into_test_train_files(in_fasta, test_out_fa, train_out_fa, + test_size=500): + """ + Split in_fasta .fa file into two files (e.g. test, train). + + """ + # Read in in_fasta. + seqs_dic = read_fasta_into_dic(in_fasta) + # Shuffle IDs. + rand_ids_list = random_order_dic_keys_into_list(seqs_dic) + c_out = 0 + TESTOUT = open(test_out_fa, "w") + TRAINOUT = open(train_out_fa, "w") + for seq_id in rand_ids_list: + seq = seqs_dic[seq_id] + if (c_out >= test_size): + TRAINOUT.write(">%s\n%s\n" % (seq_id, seq)) + else: + TESTOUT.write(">%s\n%s\n" % (seq_id, seq)) + c_out += 1 + TESTOUT.close() + TRAINOUT.close() + + +################################################################################ + +def read_fasta_into_dic(fasta_file, + seqs_dic=False, + ids_dic=False, + read_dna=False, + reject_lc=False, + convert_to_uc=False, + skip_n_seqs=True): + """ + Read in FASTA sequences, convert to RNA, store in dictionary + and return dictionary. + + >>> test_fasta = "test-data/test.fa" + >>> read_fasta_into_dic(test_fasta) + {'seq1': 'acguACGUacgu', 'seq2': 'ugcaUGCAugcaACGUacgu'} + >>> test_fasta = "test-data/test2.fa" + >>> read_fasta_into_dic(test_fasta) + {} + >>> test_fasta = "test-data/test.ensembl.fa" + >>> read_fasta_into_dic(test_fasta, read_dna=True) + {'ENST00000415118': 'GAAATAGT', 'ENST00000448914': 'ACTGGGGGATACGAAAA'} + + """ + if not seqs_dic: + seqs_dic = {} + seq_id = "" + seq = "" + + # Go through FASTA file, extract sequences. + if re.search(".+\.gz$", fasta_file): + f = gzip.open(fasta_file, 'rt') + else: + f = open(fasta_file, "r") + for line in f: + if re.search(">.+", line): + m = re.search(">(.+)", line) + seq_id = m.group(1) + # If there is a ".", take only first part of header. + # This assumes ENSEMBL header format ">ENST00000631435.1 cdna ..." + if re.search(".+\..+", seq_id): + m = re.search("(.+?)\..+", seq_id) + seq_id = m.group(1) + assert seq_id not in seqs_dic, "non-unique FASTA header \"%s\" in \"%s\"" % (seq_id, fasta_file) + if ids_dic: + if seq_id in ids_dic: + seqs_dic[seq_id] = "" + else: + seqs_dic[seq_id] = "" + elif re.search("[ACGTUN]+", line, re.I): + if seq_id in seqs_dic: + m = re.search("([ACGTUN]+)", line, re.I) + seq = m.group(1) + if reject_lc: + assert not re.search("[a-z]", seq), "lowercase characters detected in sequence \"%i\" (reject_lc=True)" %(seq_id) + if convert_to_uc: + seq = seq.upper() + # If sequences with N nucleotides should be skipped. + if skip_n_seqs: + if "n" in m.group(1) or "N" in m.group(1): + print ("WARNING: \"%s\" contains N nucleotides. Discarding sequence ... " % (seq_id)) + del seqs_dic[seq_id] + continue + # Convert to RNA, concatenate sequence. + if read_dna: + seqs_dic[seq_id] += m.group(1).replace("U","T").replace("u","t") + else: + seqs_dic[seq_id] += m.group(1).replace("T","U").replace("t","u") + f.close() + return seqs_dic + + +################################################################################ + +def random_order_dic_keys_into_list(in_dic): + """ + Read in dictionary keys, and return random order list of IDs. + + """ + id_list = [] + for key in in_dic: + id_list.append(key) + random.shuffle(id_list) + return id_list + + +################################################################################ + +def graphprot_get_param_string(params_file): + """ + Get parameter string from GraphProt .params file. + + >>> test_params = "test-data/test.params" + >>> graphprot_get_param_string(test_params) + '-epochs 20 -lambda 0.01 -R 1 -D 3 -bitsize 14 -onlyseq ' + + """ + param_string = "" + with open(params_file) as f: + for line in f: + cols = line.strip().split(" ") + param = cols[0] + setting = cols[1] + if re.search(".+:", param): + m = re.search("(.+):", line) + par = m.group(1) + if re.search("pos_train.+", line): + continue + if par == "model_type": + if setting == "sequence": + param_string += "-onlyseq " + else: + param_string += "-%s %s " %(par, setting) + else: + assert 0, "pattern matching failed for string \"%s\"" %(param) + return param_string + + +################################################################################ + +def seqs_dic_count_uc_nts(seqs_dic): + """ + Count number of uppercase nucleotides in sequences stored in sequence + dictionary. + + >>> seqs_dic = {'seq1': "acgtACGTacgt", 'seq2': 'acgtACacgt'} + >>> seqs_dic_count_uc_nts(seqs_dic) + 6 + >>> seqs_dic = {'seq1': "acgtacgt", 'seq2': 'acgtacgt'} + >>> seqs_dic_count_uc_nts(seqs_dic) + 0 + + """ + assert seqs_dic, "Given sequence dictionary empty" + c_uc = 0 + for seq_id in seqs_dic: + c_uc += len(re.findall(r'[A-Z]', seqs_dic[seq_id])) + return c_uc + + +################################################################################ + +def seqs_dic_count_lc_nts(seqs_dic): + """ + Count number of lowercase nucleotides in sequences stored in sequence + dictionary. + + >>> seqs_dic = {'seq1': "gtACGTac", 'seq2': 'cgtACacg'} + >>> seqs_dic_count_lc_nts(seqs_dic) + 10 + >>> seqs_dic = {'seq1': "ACGT", 'seq2': 'ACGTAC'} + >>> seqs_dic_count_lc_nts(seqs_dic) + 0 + + """ + assert seqs_dic, "Given sequence dictionary empty" + c_uc = 0 + for seq_id in seqs_dic: + c_uc += len(re.findall(r'[a-z]', seqs_dic[seq_id])) + return c_uc + + +################################################################################ + +def count_file_rows(in_file): + """ + Count number of file rows for given input file. + + >>> test_file = "test-data/test1.bed" + >>> count_file_rows(test_file) + 7 + >>> test_file = "test-data/empty_file" + >>> count_file_rows(test_file) + 0 + + """ + check_cmd = "cat " + in_file + " | wc -l" + output = subprocess.getoutput(check_cmd) + row_count = int(output.strip()) + return row_count + + +################################################################################ + +def bed_check_six_col_format(bed_file): + """ + Check whether given .bed file has 6 columns. + + >>> test_bed = "test-data/test1.bed" + >>> bed_check_six_col_format(test_bed) + True + >>> test_bed = "test-data/empty_file" + >>> bed_check_six_col_format(test_bed) + False + + """ + + six_col_format = False + with open(bed_file) as f: + for line in f: + cols = line.strip().split("\t") + if len(cols) == 6: + six_col_format = True + break + f.closed + return six_col_format + + +################################################################################ + +def bed_check_unique_ids(bed_file): + """ + Check whether .bed file (6 column format with IDs in column 4) + has unique column 4 IDs. + + >>> test_bed = "test-data/test1.bed" + >>> bed_check_unique_ids(test_bed) + True + >>> test_bed = "test-data/test2.bed" + >>> bed_check_unique_ids(test_bed) + False + + """ + + check_cmd = "cut -f 4 " + bed_file + " | sort | uniq -d" + output = subprocess.getoutput(check_cmd) + if output: + return False + else: + return True + + +################################################################################ + +def get_seq_lengths_from_seqs_dic(seqs_dic): + """ + Given a dictionary of sequences, return dictionary of sequence lengths. + Mapping is sequence ID -> sequence length. + """ + seq_len_dic = {} + assert seqs_dic, "sequence dictionary seems to be empty" + for seq_id in seqs_dic: + seq_l = len(seqs_dic[seq_id]) + seq_len_dic[seq_id] = seq_l + return seq_len_dic + + +################################################################################ + +def bed_get_region_lengths(bed_file): + """ + Read in .bed file, store and return region lengths in dictionary. + key : region ID (.bed col4) + value : region length (.bed col3-col2) + + >>> test_file = "test-data/test4.bed" + >>> bed_get_region_lengths(test_file) + {'CLIP1': 10, 'CLIP2': 10} + + """ + id2len_dic = {} + with open(bed_file) as f: + for line in f: + row = line.strip() + cols = line.strip().split("\t") + site_s = int(cols[1]) + site_e = int(cols[2]) + site_id = cols[3] + site_l = site_e - site_s + assert site_id not in id2len_dic, "column 4 IDs not unique in given .bed file \"%s\"" %(bed_file) + id2len_dic[site_id] = site_l + f.closed + assert id2len_dic, "No IDs read into dictionary (input file \"%s\" empty or malformatted?)" % (in_bed) + return id2len_dic + + +################################################################################ + +def graphprot_get_param_dic(params_file): + """ + Read in GraphProt .params file and store in dictionary. + key = parameter + value = parameter value + + >>> params_file = "test-data/test.params" + >>> graphprot_get_param_dic(params_file) + {'epochs': '20', 'lambda': '0.01', 'R': '1', 'D': '3', 'bitsize': '14', 'model_type': 'sequence', 'pos_train_ws_pred_median': '0.760321', 'pos_train_profile_median': '5.039610', 'pos_train_avg_profile_median_1': '4.236340', 'pos_train_avg_profile_median_2': '3.868431', 'pos_train_avg_profile_median_3': '3.331277', 'pos_train_avg_profile_median_4': '2.998667', 'pos_train_avg_profile_median_5': '2.829782', 'pos_train_avg_profile_median_6': '2.626623', 'pos_train_avg_profile_median_7': '2.447083', 'pos_train_avg_profile_median_8': '2.349919', 'pos_train_avg_profile_median_9': '2.239829', 'pos_train_avg_profile_median_10': '2.161676'} + + """ + param_dic = {} + with open(params_file) as f: + for line in f: + cols = line.strip().split(" ") + param = cols[0] + setting = cols[1] + if re.search(".+:", param): + m = re.search("(.+):", line) + par = m.group(1) + param_dic[par] = setting + f.close() + return param_dic + + +################################################################################ + +def graphprot_filter_predictions_file(in_file, out_file, + sc_thr=0): + """ + Filter GraphProt .predictions file by given score thr_sc. + """ + OUTPRED = open(out_file, "w") + with open(in_file) as f: + for line in f: + row = line.strip() + cols = line.strip().split("\t") + score = float(cols[2]) + if score < sc_thr: + continue + OUTPRED.write("%s\n" %(row)) + f.close() + OUTPRED.close() + + +################################################################################ + +def fasta_read_in_ids(fasta_file): + """ + Given a .fa file, read in header IDs in order appearing in file, + and store in list. + + >>> test_file = "test-data/test3.fa" + >>> fasta_read_in_ids(test_file) + ['SERBP1_K562_rep01_544', 'SERBP1_K562_rep02_709', 'SERBP1_K562_rep01_316'] + + """ + ids_list = [] + with open(fasta_file) as f: + for line in f: + if re.search(">.+", line): + m = re.search(">(.+)", line) + seq_id = m.group(1) + ids_list.append(seq_id) + f.close() + return ids_list + + +################################################################################ + +def graphprot_profile_calculate_avg_profile(in_file, out_file, + ap_extlr=5, + seq_ids_list=False, + method=1): + """ + Given a GraphProt .profile file, calculate average profiles and output + average profile file. + Average profile means that the position-wise scores will get smoothed + out by calculating for each position a new score, taking a sequence + window -ap_extlr to +ap_extlr relative to the position + and calculate the mean score over this window. The mean score then + becomes the new average profile score at this position. + Two different implementations of the task are given: + method=1 (new python implementation, slower + more memory but easy to read) + method=2 (old perl implementation, faster and less memory but more code) + + >>> in_file = "test-data/test2.profile" + >>> out_file1 = "test-data/test2_1.avg_profile" + >>> out_file2 = "test-data/test2_2.avg_profile" + >>> out_file4 = "test-data/test2_3.avg_profile" + >>> graphprot_profile_calculate_avg_profile(in_file, out_file1, ap_extlr=2, method=1) + >>> graphprot_profile_calculate_avg_profile(in_file, out_file2, ap_extlr=2, method=2) + >>> diff_two_files_identical(out_file1, out_file2) + True + >>> test_list = ["s1", "s2", "s3", "s4"] + >>> out_file3_exp = "test-data/test3_added_ids_exp.avg_profile" + >>> out_file3 = "test-data/test3_added_ids_out.avg_profile" + >>> graphprot_profile_calculate_avg_profile(in_file, out_file3, ap_extlr=2, method=1, seq_ids_list=test_list) + >>> diff_two_files_identical(out_file3_exp, out_file3) + True + + """ + if method == 1: + # Dictionary of lists, with list of scores (value) for each site (key). + lists_dic = {} + site_starts_dic = {} + with open(in_file) as f: + for line in f: + cols = line.strip().split("\t") + site_id = int(cols[0]) + pos = int(cols[1]) # 0-based. + score = float(cols[2]) + # Store first position of site. + if site_id not in site_starts_dic: + site_starts_dic[site_id] = pos + if site_id in lists_dic: + lists_dic[site_id].append(score) + else: + lists_dic[site_id] = [] + lists_dic[site_id].append(score) + f.close() + # Check number of IDs (# FASTA sequence IDs has to be same as # site IDs). + if seq_ids_list: + c_seq_ids = len(seq_ids_list) + c_site_ids = len(site_starts_dic) + assert c_seq_ids == c_site_ids, "# sequence IDs != # site IDs (%i != %i)" %(c_seq_ids, c_site_ids) + OUTPROF = open(out_file, "w") + # For each site, calculate average profile scores list. + max_list = [] + for site_id in lists_dic: + # Convert profile score list to average profile scores list. + aps_list = list_moving_window_average_values(lists_dic[site_id], + win_extlr=ap_extlr) + start_pos = site_starts_dic[site_id] + # Get original FASTA sequence ID. + if seq_ids_list: + site_id = seq_ids_list[site_id] + for i, sc in enumerate(aps_list): + pos = i + start_pos + 1 # make 1-based. + OUTPROF.write("%s\t%i\t%f\n" %(site_id, pos, sc)) + OUTPROF.close() + elif method == 2: + OUTPROF = open(out_file, "w") + # Old site ID. + old_id = "" + # Current site ID. + cur_id = "" + # Scores list. + scores_list = [] + site_starts_dic = {} + with open(in_file) as f: + for line in f: + cols = line.strip().split("\t") + cur_id = int(cols[0]) + pos = int(cols[1]) # 0-based. + score = float(cols[2]) + # Store first position of site. + if cur_id not in site_starts_dic: + site_starts_dic[cur_id] = pos + # Case: new site (new column 1 ID). + if cur_id != old_id: + # Process old id scores. + if scores_list: + aps_list = list_moving_window_average_values(scores_list, + win_extlr=ap_extlr) + start_pos = site_starts_dic[old_id] + seq_id = old_id + # Get original FASTA sequence ID. + if seq_ids_list: + seq_id = seq_ids_list[old_id] + for i, sc in enumerate(aps_list): + pos = i + start_pos + 1 # make 1-based. + OUTPROF.write("%s\t%i\t%f\n" %(seq_id, pos, sc)) + # Reset list. + scores_list = [] + old_id = cur_id + scores_list.append(score) + else: + # Add to scores_list. + scores_list.append(score) + f.close() + # Process last block. + if scores_list: + aps_list = list_moving_window_average_values(scores_list, + win_extlr=ap_extlr) + start_pos = site_starts_dic[old_id] + seq_id = old_id + # Get original FASTA sequence ID. + if seq_ids_list: + seq_id = seq_ids_list[old_id] + for i, sc in enumerate(aps_list): + pos = i + start_pos + 1 # make 1-based. + OUTPROF.write("%s\t%i\t%f\n" %(seq_id, pos, sc)) + OUTPROF.close() + + +################################################################################ + +def graphprot_profile_extract_peak_regions(in_file, out_file, + max_merge_dist=0, + sc_thr=0): + """ + Extract peak regions from GraphProt .profile file. + Store the peak regions (defined as regions with scores >= sc_thr) + as to out_file in 6-column .bed. + + TODO: + Add option for genomic coordinates input (+ - polarity support). + Output genomic regions instead of sequence regions. + + >>> in_file = "test-data/test4.avg_profile" + >>> out_file = "test-data/test4_out.peaks.bed" + >>> exp_file = "test-data/test4_out_exp.peaks.bed" + >>> exp2_file = "test-data/test4_out_exp2.peaks.bed" + >>> empty_file = "test-data/empty_file" + >>> graphprot_profile_extract_peak_regions(in_file, out_file) + >>> diff_two_files_identical(out_file, exp_file) + True + >>> graphprot_profile_extract_peak_regions(in_file, out_file, sc_thr=10) + >>> diff_two_files_identical(out_file, empty_file) + True + >>> graphprot_profile_extract_peak_regions(in_file, out_file, max_merge_dist=2) + >>> diff_two_files_identical(out_file, exp2_file) + True + + """ + + OUTPEAKS = open(out_file, "w") + # Old site ID. + old_id = "" + # Current site ID. + cur_id = "" + # Scores list. + scores_list = [] + site_starts_dic = {} + with open(in_file) as f: + for line in f: + cols = line.strip().split("\t") + cur_id = cols[0] + pos = int(cols[1]) # 0-based. + score = float(cols[2]) + # Store first position of site. + if cur_id not in site_starts_dic: + # If first position != zero, we assume positions are 1-based. + if pos != 0: + # Make index 0-based. + site_starts_dic[cur_id] = pos - 1 + else: + site_starts_dic[cur_id] = pos + # Case: new site (new column 1 ID). + if cur_id != old_id: + # Process old id scores. + if scores_list: + # Extract peaks from region. + peak_list = list_extract_peaks(scores_list, + max_merge_dist=max_merge_dist, + coords="bed", + sc_thr=sc_thr) + start_pos = site_starts_dic[old_id] + # Print out peaks in .bed format. + for l in peak_list: + peak_s = start_pos + l[0] + peak_e = start_pos + l[1] + site_id = "%s,%i" %(old_id, l[2]) + OUTPEAKS.write("%s\t%i\t%i\t%s\t%f\t+\n" %(old_id, peak_s, peak_e, site_id, l[3])) + # Reset list. + scores_list = [] + old_id = cur_id + scores_list.append(score) + else: + # Add to scores_list. + scores_list.append(score) + f.close() + # Process last block. + if scores_list: + # Extract peaks from region. + peak_list = list_extract_peaks(scores_list, + max_merge_dist=max_merge_dist, + coords="bed", + sc_thr=sc_thr) + start_pos = site_starts_dic[old_id] + # Print out peaks in .bed format. + for l in peak_list: + peak_s = start_pos + l[0] + peak_e = start_pos + l[1] + site_id = "%s,%i" %(old_id, l[2]) # best score also 1-based. + OUTPEAKS.write("%s\t%i\t%i\t%s\t%f\t+\n" %(old_id, peak_s, peak_e, site_id, l[3])) + OUTPEAKS.close() + + +################################################################################ + +def list_extract_peaks(in_list, + max_merge_dist=0, + coords="list", + sc_thr=0): + """ + Extract peak regions from list. + Peak region is defined as region >= score threshold. + + coords=bed : peak start 0-based, peak end 1-based. + coords=list : peak start 0-based, peak end 0-based. + + >>> test_list = [-1, 0, 2, 4.5, 1, -1, 5, 6.5] + >>> list_extract_peaks(test_list) + [[1, 4, 3, 4.5], [6, 7, 7, 6.5]] + >>> list_extract_peaks(test_list, sc_thr=2) + [[2, 3, 3, 4.5], [6, 7, 7, 6.5]] + >>> list_extract_peaks(test_list, sc_thr=2, coords="bed") + [[2, 4, 4, 4.5], [6, 8, 8, 6.5]] + >>> list_extract_peaks(test_list, sc_thr=10) + [] + >>> test_list = [2, -1, 3, -1, 4, -1, -1, 6, 9] + >>> list_extract_peaks(test_list, max_merge_dist=2) + [[0, 4, 4, 4], [7, 8, 8, 9]] + >>> list_extract_peaks(test_list, max_merge_dist=3) + [[0, 8, 8, 9]] + + """ + # Check. + assert len(in_list), "Given list is empty" + # Peak regions list. + peak_list = [] + # Help me. + inside = False + pr_s = 0 + pr_e = 0 + pr_top_pos = 0 + pr_top_sc = -100000 + for i, sc in enumerate(in_list): + # Part of peak region? + if sc >= sc_thr: + # At peak start. + if not inside: + pr_s = i + pr_e = i + inside = True + else: + # Inside peak region. + pr_e = i + # Store top position. + if sc > pr_top_sc: + pr_top_sc = sc + pr_top_pos = i + else: + # Before was peak region? + if inside: + # Store peak region. + #peak_infos = "%i,%i,%i,%f" %(pr_s, pr_e, pr_top_pos, pr_top_sc) + peak_infos = [pr_s, pr_e, pr_top_pos, pr_top_sc] + peak_list.append(peak_infos) + inside = False + pr_top_pos = 0 + pr_top_sc = -100000 + # If peak at the end, also report. + if inside: + # Store peak region. + peak_infos = [pr_s, pr_e, pr_top_pos, pr_top_sc] + peak_list.append(peak_infos) + # Merge peaks. + if max_merge_dist and len(peak_list) > 1: + iterate = True + while iterate: + merged_peak_list = [] + added_peaks_dic = {} + peaks_merged = False + for i, l in enumerate(peak_list): + if i in added_peaks_dic: + continue + j = i + 1 + # Last element. + if j == len(peak_list): + if i not in added_peaks_dic: + merged_peak_list.append(peak_list[i]) + break + # Compare two elements. + new_peak = [] + if (peak_list[j][0] - peak_list[i][1]) <= max_merge_dist: + peaks_merged = True + new_top_pos = peak_list[i][2] + new_top_sc = peak_list[i][3] + if peak_list[i][3] < peak_list[j][3]: + new_top_pos = peak_list[j][2] + new_top_sc = peak_list[j][3] + new_peak = [peak_list[i][0], peak_list[j][1], new_top_pos, new_top_sc] + # If two peaks were merged. + if new_peak: + merged_peak_list.append(new_peak) + added_peaks_dic[i] = 1 + added_peaks_dic[j] = 1 + else: + merged_peak_list.append(peak_list[i]) + added_peaks_dic[i] = 1 + if not peaks_merged: + iterate = False + peak_list = merged_peak_list + peaks_merged = False + # If peak coordinates should be in .bed format, make peak ends 1-based. + if coords == "bed": + for i in range(len(peak_list)): + peak_list[i][1] += 1 + peak_list[i][2] += 1 # 1-base best score position too. + return peak_list + + +################################################################################ + +def bed_peaks_to_genomic_peaks(peak_file, genomic_peak_file, genomic_sites_bed, print_rows=False): + """ + Given a .bed file of sequence peak regions (possible coordinates from + 0 to length of s), convert peak coordinates to genomic coordinates. + Do this by taking genomic regions of sequences as input. + + >>> test_in = "test-data/test.peaks.bed" + >>> test_exp = "test-data/test_exp.peaks.bed" + >>> test_out = "test-data/test_out.peaks.bed" + >>> gen_in = "test-data/test.peaks_genomic.bed" + >>> bed_peaks_to_genomic_peaks(test_in, test_out, gen_in) + >>> diff_two_files_identical(test_out, test_exp) + True + + """ + # Read in genomic region info. + id2row_dic = {} + + with open(genomic_sites_bed) as f: + for line in f: + row = line.strip() + cols = line.strip().split("\t") + site_id = cols[3] + assert site_id not in id2row_dic, "column 4 IDs not unique in given .bed file \"%s\"" %(args.genomic_sites_bed) + id2row_dic[site_id] = row + f.close() + + # Read in peaks file and convert coordinates. + OUTPEAKS = open(genomic_peak_file, "w") + with open(peak_file) as f: + for line in f: + cols = line.strip().split("\t") + site_id = cols[0] + site_s = int(cols[1]) + site_e = int(cols[2]) + site_id2 = cols[3] + site_sc = float(cols[4]) + assert re.search(".+,.+", site_id2), "regular expression failed for ID \"%s\"" %(site_id2) + m = re.search(".+,(\d+)", site_id2) + sc_pos = int(m.group(1)) # 1-based. + assert site_id in id2row_dic, "site ID \"%s\" not found in genomic sites dictionary" %(site_id) + row = id2row_dic[site_id] + rowl = row.split("\t") + gen_chr = rowl[0] + gen_s = int(rowl[1]) + gen_e = int(rowl[2]) + gen_pol = rowl[5] + new_s = site_s + gen_s + new_e = site_e + gen_s + new_sc_pos = sc_pos + gen_s + if gen_pol == "-": + new_s = gen_e - site_e + new_e = gen_e - site_s + new_sc_pos = gen_e - sc_pos + 1 # keep 1-based. + new_row = "%s\t%i\t%i\t%s,%i\t%f\t%s" %(gen_chr, new_s, new_e, site_id, new_sc_pos, site_sc, gen_pol) + OUTPEAKS.write("%s\n" %(new_row)) + if print_rows: + print(new_row) + OUTPEAKS.close() + + +################################################################################ + +def diff_two_files_identical(file1, file2): + """ + Check whether two files are identical. Return true if diff reports no + differences. + + >>> file1 = "test-data/file1" + >>> file2 = "test-data/file2" + >>> diff_two_files_identical(file1, file2) + True + >>> file1 = "test-data/test1.bed" + >>> diff_two_files_identical(file1, file2) + False + + """ + same = True + check_cmd = "diff " + file1 + " " + file2 + output = subprocess.getoutput(check_cmd) + if output: + same = False + return same + + +################################################################################ + +
--- a/graphprot_predict_profile.xml Fri May 25 12:17:44 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,227 +0,0 @@ -<tool id="graphprot_predict_profile" name="GraphProt predict profile" version="1.1.7"> - <description>- Predict RBP binding profiles</description> - <requirements> - <requirement type="package" version="1.1.7">graphprot</requirement> - </requirements> - <command><![CDATA[ - #if $select_model.model_selector == 'select_model_from_repo': - mkdir -p ./model && - tar -zxvf '$__tool_directory__/data/${select_model.repo_model}.tar.gz' -C ./model && - #end if - perl '$__tool_directory__/graphprot_predict_profile_wrapper.pl' - -fasta '$fasta_file' - #if $select_model.model_selector == 'select_model_from_history': - -model '$select_model.model_file' - #if $select_model.set_params.set_params_selector == 'supply_params_file': - -params '$select_model.set_params.params_file' - #elif $select_model.set_params.set_params_selector == 'manual_params_setting': - #if $select_model.set_params.model_type.model_type_selector == 'sequence': - -onlyseq - #elif $select_model.set_params.model_type.model_type_selector == 'structure': - -abstraction $select_model.set_params.model_type.gp_abstraction - #end if - -R $select_model.set_params.gp_r - -D $select_model.set_params.gp_d - -bitsize $select_model.set_params.gp_bitsize - -lambda $select_model.set_params.gp_lambda - -epochs $select_model.set_params.gp_epochs - #if $select_model.set_params.gev_options.distr_my - -distr-my $select_model.set_params.gev_options.distr_my - #end if - #if $select_model.set_params.gev_options.distr_sigma - -distr-sigma $select_model.set_params.gev_options.distr_sigma - #end if - #if $select_model.set_params.gev_options.distr_xi - -distr-xi $select_model.set_params.gev_options.distr_xi - #end if - #end if - #elif $select_model.model_selector == 'select_model_from_repo': - -model './model/${select_model.repo_model}.model' - -params './model/${select_model.repo_model}.params' - #end if - $peak_region_options.p50_output - #if $peak_region_options.merge_dist - -merge-dist $peak_region_options.merge_dist - #end if - #if $peak_region_options.p_val_thr - -thr-p $peak_region_options.p_val_thr - #end if - #if $peak_region_options.score_thr - -thr-sc $peak_region_options.score_thr - #end if - ]]></command> - <inputs> - <param name="fasta_file" type="data" format="fasta" label="Input FASTA file" argument="-fasta" - help="FASTA file containing sequences to predict binding profiles on"/> - - <conditional name="select_model"> - <param name="model_selector" type="select" label="Select GraphProt model" - help="Select GraphProt model for binding profile prediction"> - <option value="select_model_from_history" selected="true">Select model from history</option> - <option value="select_model_from_repo">Select model from repository</option> - </param> - <when value="select_model_from_history"> - <param name="model_file" type="data" format="data" label="GraphProt model file" argument="-model" - help="Predict binding profile for the given GraphProt RBP model"/> - <conditional name="set_params"> - <param name="set_params_selector" type="select" label="Set model parameters"> - <option value="supply_params_file" selected="true">Select parameter file from history</option> - <option value="manual_params_setting">Manually set model parameters</option> - </param> - <when value="supply_params_file"> - <param name="params_file" type="data" format="txt" - label="Model parameter file" argument="-params" - help="Parameter file containing model parameters"/> - </when> - <when value="manual_params_setting"> - <conditional name="model_type"> - <param name="model_type_selector" type="select" label="Select model type"> - <option value="sequence" selected="true">Supplied model is a sequence model</option> - <option value="structure">Supplied model is a structure model</option> - </param> - <when value="sequence"/> - <when value="structure"> - <param name="gp_abstraction" type="integer" value="3" argument="-abstraction" - label="RNAshapes abstraction level for RNA structure graphs"/> - </when> - </conditional> - <param name="gp_r" type="integer" value="1" min="0" max="4" - label="GraphProt radius" argument="-R"/> - <param name="gp_d" type="integer" value="4" min="0" max="6" - label="GraphProt distance" argument="-D"/> - <param name="gp_bitsize" type="integer" value="14" - label="GraphProt bitsize used for feature encoding" argument="-bitsize"/> - <param name="gp_lambda" type="float" value="10e-6" - label="SGD parameter lambda for classification" argument="-lambda"/> - <param name="gp_epochs" type="integer" value="10" - label="SGD parameter epochs for classification" argument="-epochs"/> - <section name="gev_options" title="GEV distribution parameters for signifying GraphProt scores"> - <param name="distr_my" type="float" optional="True" - label="GEV distribution parameter my" argument="-distr-my"/> - <param name="distr_sigma" type="float" optional="True" - label="GEV distribution parameter sigma" argument="-distr-sigma"/> - <param name="distr_xi" type="float" optional="True" - label="GEV distribution parameter xi" argument="-distr-xi"/> - </section> - </when> - </conditional> - </when> - <when value="select_model_from_repo"> - <param name="repo_model" type="select" label="Select model" help="Select model from a list of pre-trained GraphProt models"> - <option value="EWSR1_eCLIP_K562_ENCSR887LPK" selected="true">EWSR1_eCLIP_K562_ENCSR887LPK.model</option> - <option value="FMR1_eCLIP_K562_ENCSR331VNX">FMR1_eCLIP_K562_ENCSR331VNX.model</option> - <option value="HNRNPC_eCLIP_HepG2_ENCSR550DVK">HNRNPC_eCLIP_HepG2_ENCSR550DVK.model</option> - <option value="HUR_PAR-CLIP_HEK293_Mukherjee">HUR_PAR-CLIP_HEK293_Mukherjee.model</option> - <option value="IGF2BP1-3_PAR-CLIP_HEK293_Hafner">IGF2BP1-3_PAR-CLIP_HEK293_Hafner.model</option> - <option value="IGF2BP1-3_PAR-CLIP_HEK293_Hafner_structure">IGF2BP1-3_PAR-CLIP_HEK293_Hafner_structure.model</option> - <option value="KHDRBS1_eCLIP_K562_ENCSR628IDK">KHDRBS1_eCLIP_K562_ENCSR628IDK.model</option> - <option value="KHDRBS1_eCLIP_K562_ENCSR628IDK_structure">KHDRBS1_eCLIP_K562_ENCSR628IDK_structure.model</option> - <option value="PUM2_PAR-CLIP_HEK293_Hafner">PUM2_PAR-CLIP_HEK293_Hafner.model</option> - <option value="PUM2_eCLIP_K562_exonized_3utr">PUM2_eCLIP_K562_exonized_3utr.model</option> - <option value="QKI_PAR-CLIP_HEK293_Hafner">QKI_PAR-CLIP_HEK293_Hafner.model</option> - <option value="QKI_eCLIP_HepG2_ENCSR570WLM">EWSR1_eCLIP_K562_ENCSR887LPK.model</option> - <option value="QKI_eCLIP_HepG2_ENCSR570WLM_structure">QKI_eCLIP_HepG2_ENCSR570WLM_structure.model</option> - </param> - </when> - </conditional> - <section name="peak_region_options" title="Peak region options"> - <param name="merge_dist" type="integer" optional="True" - label="Maximum distance between two peak regions for merging" argument="-merge-dist" - help="By default all non-overlapping regions will be reported. E.g. a distance of 1 means that two regions above the set threshold (score or p-value) will be merged if they is 1 nucleotide that separates the two regions"/> - <param name="p_val_thr" type="float" optional="True" - label="Set p-value threshold for reporting peak regions" - help="Regions with p-value lower or equal the given value are reported. If no distribution parameters are given (either manually or in .params file), no p-values will be calculated and peak regions will be filtered by their peak scores instead (default: 0.05)"/> - <param name="score_thr" type="float" optional="True" - label="Set GraphProt peak score threshold for reporting peak regions" - help="Regions with peak score higher or equal the given value are reported. If distribution parameters are given (either manually or in .params file), p-value threshold will be used instead of the peak score threshold for filtering (default: 0)"/> - <param name="p50_output" label="Also output p50 score filtered peak regions file" type="boolean" - truevalue="-p50-out" falsevalue="" checked="False" - help="Output is a peak regions BED file using the best average score found in at least 50 % of the positive training sites (p50) as threshold for defining peak regions. NOTE that if the score is not given in .params file, an empty file will be output if selected."/> - </section> - </inputs> - <outputs> - <data format="txt" name="average_profile_outfile" label="${tool.name} on ${on_string} (average profile)" from_work_dir="GraphProt.average_profile"/> - <data format="bed" name="peak_regions_outfile" label="${tool.name} on ${on_string} (peak regions)" from_work_dir="GraphProt.peak_regions.bed"/> - <data format="bed" name="peak_regions_p50_outfile" label="${tool.name} on ${on_string} (peak regions p50)" from_work_dir="GraphProt.peak_regions_p50.bed"/> - </outputs> - <tests> - <test> - <param name="fasta_file" value="test.fa" ftype="fasta"/> - <param name="model_selector" value="select_model_from_history"/> - <param name="model_file" value="test.model"/> - <param name="set_params_selector" value="supply_params_file"/> - <param name="params_file" value="test.params"/> - <param name="p50_output" value="True"/> - <output name="average_profile_outfile" file="GraphProt_predict_profile_test_out1.average_profile"/> - <output name="peak_regions_outfile" file="GraphProt_predict_profile_test_out1.peak_regions.bed"/> - <output name="peak_regions_p50_outfile" file="GraphProt_predict_profile_test_out1.peak_regions_p50.bed"/> - </test> - <test> - <param name="fasta_file" value="test.fa" ftype="fasta"/> - <param name="model_selector" value="select_model_from_history"/> - <param name="model_file" value="test.model"/> - <param name="set_params_selector" value="manual_params_setting"/> - <param name="model_type_selector" value="sequence"/> - <param name="gp_r" value="1"/> - <param name="gp_d" value="4"/> - <param name="gp_epochs" value="20"/> - <param name="gp_lambda" value="0.001"/> - <param name="gp_bitsize" value="14"/> - <param name="merge_dist" value="1"/> - <param name="score_thr" value="1"/> - <output name="average_profile_outfile" file="GraphProt_predict_profile_test_out2.average_profile"/> - <output name="peak_regions_outfile" file="GraphProt_predict_profile_test_out2.peak_regions.bed"/> - </test> - <test> - <param name="fasta_file" value="test.fa" ftype="fasta"/> - <param name="model_selector" value="select_model_from_history"/> - <param name="model_file" value="structure_test.model"/> - <param name="set_params_selector" value="supply_params_file"/> - <param name="params_file" value="structure_test.params"/> - <param name="model_type_selector" value="structure"/> - <param name="gp_abstraction" value="3"/> - <param name="score_thr" value="2"/> - <output name="average_profile_outfile" file="GraphProt_predict_profile_test_out3.average_profile"/> - <output name="peak_regions_outfile" file="GraphProt_predict_profile_test_out3.peak_regions.bed"/> - </test> - <test> - <param name="fasta_file" value="test.fa" ftype="fasta"/> - <param name="model_selector" value="select_model_from_repo"/> - <param name="repo_model" value="FMR1_eCLIP_K562_ENCSR331VNX"/> - <param name="p50_output" value="True"/> - <output name="average_profile_outfile" file="GraphProt_predict_profile_test_out4.average_profile"/> - <output name="peak_regions_outfile" file="GraphProt_predict_profile_test_out4.peak_regions.bed"/> - <output name="peak_regions_p50_outfile" file="GraphProt_predict_profile_test_out4.peak_regions_p50.bed"/> - </test> - - </tests> - <help> - -Use GraphProt (-action predict_profile) to predict binding profiles for a given RBP model (supplied as .model and .params file) on a given set of FASTA sequences. After predicting position-wise scores, the scores are averaged over small windows (11 nt with averaged score position in center) to smooth out the profiles and peak regions are extracted based on the set thresholds (p-value or score) and merge distance. - -**Output files** - -The procedure has three output files (third is optional): - -1) An average_profile file containing averaged position-scores over all supplied sequences - -2) A peak regions BED file which contains peak-scoring regions above the supplied threshold (p-value default: 0.05, score default: 0) - -3) A peak regions BED file using the best average score found in at least 50 % of the positive training sites (p50). NOTE that this requires the p50 score to be given in the .params file, otherwise if set an empty file will be output. - -**Model selection** - -The GraphProt model used for profile prediction can either be uploaded to history or chosen from an example collection of models (Select model from repository). For the repository models, the corresponding parameter file is selected automatically, providing all model parameters necessary for prediction and p-value calculation. If you choose to upload a model to the history, it is recommended to use the corresponding .params file for automatically setting the model parameters. Otherwise the model parameters have to be entered manually. - -**p-value calculation** - -Signifying the GraphProt scores is done by fitting a generalized extreme value (GEV) distribution on a set of scores derived from 10000 transcript sequences for each GraphProt model. The GEV distribution has three parameters: my (location), sigma (scale), and xi (shape). The fitted parameter values usually are read in from the .params file, but can also be entered manually. Parameter fitting was done in R using the minpack.lm_ package, using the probability density function (PDF) described here_. If no GEV parameter values are specified (either in .params file or manually), p-value calculation for the scores will be skipped and the peak regions will be extracted based on the set threshold score. - -.. _here: https://en.wikipedia.org/wiki/Generalized_extreme_value_distribution -.. _minpack.lm: https://cran.r-project.org/web/packages/minpack.lm - - </help> - <citations> - <citation type="doi">10.1186/gb-2014-15-1-r17</citation> - </citations> -</tool>
--- a/graphprot_predict_profile_wrapper.pl Fri May 25 12:17:44 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,764 +0,0 @@ -#!/usr/bin/perl - -use strict; -use warnings; -use Getopt::Long; -use Pod::Usage; -use Cwd qw(getcwd abs_path); -use List::Util qw(sum); - -=head1 NAME - -=head1 SYNOPSIS - -Galaxy wrapper script for GraphProt (-action predict_profile) to compute -the binding profile for a given model on a given set of sequences provided -in FASTA format. After profile prediction, average profiles get computed, -scores signified and binding peak regions extracted. The score signification -is done using the provided fitted GEV parameters, either from .params file -or manually set. If score threshold is set (-thr-sc), p-value assignment -will be skipped and set score threshold will be used to extract peak -regions. NOTE: Additional lines .params file are used to store and get -GEV parameters, as well as type of model (model_type: sequence|structure). -Also, this wrapper currently works for classification mode only. - -PARAMETERS: - - -help|h display help page - -fasta Input FASTA file (option -fasta) - -model Input .model file (option -model) - -params Input .params file - NOTE: uses .params file with additional - parameters - Manually set parameters (below) will override - found settings in .params file - -data-id Data ID (option -prefix) - -GraphProt model parameters (by default get from .params file): - - -onlyseq Set if model is a sequence model - -R GraphProt model R parameter - -D GraphProt model D parameter - -epochs GraphProt model epochs parameter - -lambda GraphProt model lambda parameter - -bitsize GraphProt model bitsize parameter - -abstraction GraphProt model RNAshapes abstraction level - parameter (set for structure models) - -Peak region extraction parameters: - - -thr-sc Score threshold for extracting peak regions - By default p-value of 0.05 is used. If no p-value - calculation possible, -thr-sc is used with default: 0 - -thr-p p-value threshold for extracting peak regions - By default, peak regions with p = 0.05 are extracted, - as well as p50 score peak regions (if info given) - Default: 0.05 - -merge-dist Maximum merge distance for nearby peak regions - Default: report all non-overlapping regions - -p50-out Output p50 score filtered peak regions BED file - default: false - -GEV distribution parameters: - - -distr-my GEV distribution my parameter for calculating p-values - from scores - -distr-sigma GEV distrubution sigma parameter for calculating - p-values from scores - -distr-xi GEV distribution xi parameter for calculating p-values - from scores - -ap-extlr Used average profile left right extension for - averaging scores, which were used for distribution - fitting. NOTE: usually a value of 5 was used for - for getting GEV distribution and parameters. If you - choose a different value here, calculated p-values - will be wrong! - default : 5 - - -=head1 DISCRIPTION - -5) Write manual -6) add output p50 file with NOTE - -6) put GP into rna_tools - -NOTE: -Additional lines .params file used to store and get gev parameters, as well -as type of model (model_type: sequence|structure). - -Example .params content: -epochs: 20 -lambda: 0.001 -R: 1 -D: 4 -bitsize: 14 -model_type: sequence -#ADDITIONAL MODEL PARAMETERS -ap_extlr: 5 -gev_my: -2.5408 -gev_sigma: 1.6444 -gev_xi: -0.1383 -p50_score: 6.51534 -p50_p_val: 0.0009059744 - -=cut - -############################ -# COMMAND LINE CHECKING. -############################ - -# Command line argument variables. -my ($i_help, $i_fasta, $i_model, $i_params, $i_data_id, $i_thr_sc, $i_thr_p, $i_max_merge_dist, $i_p50_out, $i_gp_r, $i_gp_d, $i_gp_epochs, $i_gp_lambda, $i_gp_bitsize, $i_gp_abstr, $i_gp_onlyseq, $i_distr_my, $i_distr_sigma, $i_distr_xi, $i_ap_extlr); - -# Parse the command line. -GetOptions ( "help|h" => \$i_help, - "fasta:s" => \$i_fasta, - "model:s" => \$i_model, - "params:s" => \$i_params, - "data-id:s" => \$i_data_id, - "thr-sc:f" => \$i_thr_sc, - "thr-p:f" => \$i_thr_p, - "p50-out" => \$i_p50_out, - "merge-dist:i" => \$i_max_merge_dist, - "R:i" => \$i_gp_r, - "D:i" => \$i_gp_d, - "epochs:i" => \$i_gp_epochs, - "lambda:f" => \$i_gp_lambda, - "bitsize:i" => \$i_gp_bitsize, - "abstr:i" => \$i_gp_abstr, - "onlyseq" => \$i_gp_onlyseq, - "distr-my:f" => \$i_distr_my, - "distr-sigma:f" => \$i_distr_sigma, - "distr-xi:f" => \$i_distr_xi, - "ap-extlr:i" => \$i_ap_extlr ) or pod2usage(1); - -# Check. -pod2usage(1) if $i_help; -($i_fasta and $i_model) or pod2usage "ERROR: -fasta, -model are mandatory"; -if ($i_distr_my or $i_distr_sigma or $i_distr_xi) { - ($i_distr_my and $i_distr_sigma and $i_distr_xi) or pod2usage "ERROR: expects all three distribution parameters to be set"; -} - -####################### -# SET PARAMETERS. -####################### - -# Prefix. -my $data_id = "GraphProt"; -if ($i_data_id) { - $data_id = $i_data_id; -} -my $thr_sc = 0; -if ($i_thr_sc) { - $thr_sc = $i_thr_sc; -} -my $thr_p = 0.05; -if ($i_thr_p) { - $thr_p = $i_thr_p; -} -my $ap_extlr = 5; -if ($i_ap_extlr) { - $ap_extlr = $i_ap_extlr; -} -my $max_merge_dist = 0; -if ($i_max_merge_dist) { - $max_merge_dist = $i_max_merge_dist; -} - -# Get parameters from .params file. -my %params; -if ($i_params) { - open(IN, $i_params) or die "Cannot open $i_params: $!"; - while(<IN>) { - next if ($_ =~ /^#/); - if ($_ =~ /(.+):\s(.+)/) { - $params{$1} = $2; - } - } - close IN; -} - -# Create GP parameter string. -my $params_string = ""; -# -onlyseq -my $model_type = "structure"; -if (exists $params{"model_type"}) { - if ($params{"model_type"} eq "sequence") { - $params_string .= " -onlyseq"; - $model_type = "sequence"; - } -} elsif ($i_gp_onlyseq) { - $params_string .= " -onlyseq"; - $model_type = "sequence"; -} -# -R -if ($i_gp_r) { - $params_string .= " -R $i_gp_r"; -} elsif (exists $params{"R"}) { - my $v = $params{"R"}; - $params_string .= " -R $v"; -} else { - die "ERROR: -R needs to be set"; -} -# -D -if ($i_gp_d) { - $params_string .= " -D $i_gp_d"; -} elsif (exists $params{"D"}) { - my $v = $params{"D"}; - $params_string .= " -D $v"; -} else { - die "ERROR: -D needs to be set"; -} -# -epochs -if ($i_gp_epochs) { - $params_string .= " -epochs $i_gp_epochs"; -} elsif (exists $params{"epochs"}) { - my $v = $params{"epochs"}; - $params_string .= " -epochs $v"; -} else { - die "ERROR: -epochs needs to be set"; -} -# -lambda -if ($i_gp_lambda) { - $params_string .= " -lambda $i_gp_lambda"; -} elsif (exists $params{"lambda"}) { - my $v = $params{"lambda"}; - $params_string .= " -lambda $v"; -} else { - die "ERROR: -lambda needs to be set"; -} -# -bitsize -if ($i_gp_bitsize) { - $params_string .= " -bitsize $i_gp_bitsize"; -} elsif (exists $params{"bitsize"}) { - my $v = $params{"bitsize"}; - $params_string .= " -bitsize $v"; -} else { - die "ERROR: -bitsize needs to be set"; -} -# -abstraction -if ($i_gp_abstr) { - $params_string .= " -bitsize $i_gp_abstr"; - die "ERROR: -abstraction set with -onlyseq" unless ($model_type eq "structure"); -} elsif (exists $params{"abstraction"}) { - my $v = $params{"abstraction"}; - $params_string .= " -abstraction $v"; - die "ERROR: -abstraction set with -onlyseq" unless ($model_type eq "structure"); -} - -# Distribution parameters. -my ($distr_my, $distr_sigma, $distr_xi); -if ($i_distr_my) { - $distr_my = $i_distr_my; -} elsif (exists $params{"gev_my"}) { - $distr_my = $params{"gev_my"}; -} -if ($i_distr_sigma) { - $distr_sigma = $i_distr_sigma; -} elsif (exists $params{"gev_sigma"}) { - $distr_sigma = $params{"gev_sigma"}; -} -if ($i_distr_xi) { - $distr_xi = $i_distr_xi; -} elsif (exists $params{"gev_xi"}) { - $distr_xi = $params{"gev_xi"}; -} -# Average profile extension parameter. -if (exists $params{"ap_extlr"}) { - $ap_extlr = $params{"ap_extlr"}; -} - -print STDOUT "model_type: $model_type\n"; -print STDOUT "ap_extlr: $ap_extlr\n"; - -if ($distr_my and $distr_sigma and $distr_xi) { - print STDOUT "distr_my: $distr_my\n"; - print STDOUT "distr_sigma: $distr_sigma\n"; - print STDOUT "distr_xi: $distr_xi\n"; -} -print STDOUT "max_merge_dist: $max_merge_dist\n"; - -# p50 filter score. -my $p50_sc; -if (exists $params{"p50_score"}) { - $p50_sc = $params{"p50_score"}; - print STDOUT "p50_score: $p50_sc\n"; -} -# p50 p-value. -my $p50_p; -if (exists $params{"p50_p_val"}) { - $p50_p = $params{"p50_p_val"}; - print STDOUT "p50_p_val: $p50_p\n"; -} - - - -################################## -# RUN GP PROFILE PREDICTION. -################################## - -# Read in FASTA file headers. -my @fasta_ids; -my $headers = qx/grep ">" $i_fasta/; -while ($headers =~ />(.+?)\n/g) { - push(@fasta_ids,$1); -} - -# Run GP profile prediction. -my $gp_call = "GraphProt.pl -action predict_profile -model $i_model -fasta $i_fasta -prefix $data_id $params_string"; -print STDOUT "GraphProt call: $gp_call\n"; -# &> profile_prediction.log -qx/$gp_call/; - - -#################################### -# CALCULATE AVERAGE PROFILE. -#################################### - -# Calculate .average_profile from GraphProt .profile file. -# Also add p-value column if distr parameters set. -my $add_p = 0; -if ($distr_my and $distr_sigma and $distr_xi) { - $add_p = 1; -} - -# Average_profile: 1-based, FASTA headers as IDs, using ap_extlr for averaging scores. -my $profile = "$data_id.profile"; -my $average_profile = "$data_id.average_profile"; -# Calculate window size. -my $win = $ap_extlr * 2 + 1; - -open (IN, $profile) or die "Cannot open $profile: $!\n"; -open (OUT, '>', $average_profile) or die "Cannot open $average_profile: $!"; - -# Old ID. -my $old_id = "-"; -# Current ID. -my $cur_id = "-"; -# Start position of the window. -my $pos_inc = 0; -# Score array. -my @scores; -# Input row counter. -my $c_in = 0; -# Output row counter. -my $c_out = 0; - -while (<IN>) { - - if ($_ =~ /(.+?)\t\d+?\t(.+?)\n/) { - - $cur_id = $1; - my $score = $2; - $c_in++; - - # Case: New refseq ID / new paragraph. - if ($cur_id ne $old_id) { - - # Print remaining entries at the end of former paragraph. - while (scalar(@scores) >= ($ap_extlr + 1)) { - # Calculate avg array score. - my $mean = array_mean(@scores); - $c_out++; - $pos_inc++; - if ($add_p) { - my $y = exp(-1*(1 + ( ($mean-$distr_my)/$distr_sigma )*$distr_xi)**(-1/$distr_xi)); - my $p = sprintf("%.8f", (1-$y)); - print OUT "$fasta_ids[$old_id]\t$pos_inc\t$mean\t$p\n"; - } else { - print OUT "$fasta_ids[$old_id]\t$pos_inc\t$mean\n"; - } - # Remove old score from beginning. - shift(@scores); - } - - # Reset for new paragraph. - $pos_inc = 0; - @scores = (); - $old_id = $cur_id; - # Save first score. - push(@scores, $score); - next; - - } - - # Push score in array for average calculation. - push(@scores, $score); - - # Case: array smaller $win. - if (scalar(@scores) < $win) { - # Subcase: array more than half size, start with calculation. - if (scalar(@scores) >= ($ap_extlr + 1)) { - # Calculate avg array score. - my $mean = array_mean(@scores); - $c_out++; - $pos_inc++; - if ($add_p) { - my $y = exp(-1*(1 + ( ($mean-$distr_my)/$distr_sigma )*$distr_xi)**(-1/$distr_xi)); - my $p = sprintf("%.8f", (1-$y)); - print OUT "$fasta_ids[$cur_id]\t$pos_inc\t$mean\t$p\n"; - } else { - print OUT "$fasta_ids[$cur_id]\t$pos_inc\t$mean\n"; - } - } - next; - } - - # Case: array has $win size. - if (scalar(@scores) == $win) { - # Calculate avg array score. - my $mean = array_mean(@scores); - $c_out++; - $pos_inc++; - if ($add_p) { - my $y = exp(-1*(1 + ( ($mean-$distr_my)/$distr_sigma )*$distr_xi)**(-1/$distr_xi)); - my $p = sprintf("%.8f", (1-$y)); - print OUT "$fasta_ids[$cur_id]\t$pos_inc\t$mean\t$p\n"; - } else { - print OUT "$fasta_ids[$cur_id]\t$pos_inc\t$mean\n"; - } - # Remove old score from beginning. - shift(@scores); - next; - } - } -} - -# Print remaining entries at the end of last section. -while (scalar(@scores) >= ($ap_extlr + 1)) { - # Calculate avg array score. - my $mean = array_mean(@scores); - $c_out++; - $pos_inc++; - if ($add_p) { - my $y = exp(-1*(1 + ( ($mean-$distr_my)/$distr_sigma )*$distr_xi)**(-1/$distr_xi)); - my $p = sprintf("%.8f", (1-$y)); - print OUT "$fasta_ids[$cur_id]\t$pos_inc\t$mean\t$p\n"; - } else { - print OUT "$fasta_ids[$cur_id]\t$pos_inc\t$mean\n"; - } - # Remove old score from beginning. - shift(@scores); -} -close IN; -close OUT; - -qx/rm -f $profile/; - - -######################### -# GET PEAK REGIONS. -######################### - - -my $p50_peaks_bed_out = $data_id . ".peak_regions_p50.bed"; -my $peaks_bed_out = $data_id . ".peak_regions.bed"; - -# If p-values were calculated, use set p-value to get peak regions. -if ($add_p) { - extract_peak_regions_from_p_values($average_profile, $peaks_bed_out, $max_merge_dist, $thr_p); - # If p50-out set. - if ($i_p50_out) { - # If p50 p-value present, also get peak regions file for this threshold. - if ($p50_p) { - extract_peak_regions_from_p_values($average_profile, $p50_peaks_bed_out, $max_merge_dist, $p50_p); - } else { - qx/touch $p50_peaks_bed_out/; - } - } -} else { - # If no p-values available, use score threshold for defining peak regions. - extract_peak_regions_from_scores($average_profile, $peaks_bed_out, $max_merge_dist, $thr_sc); - # If p50-out set. - if ($i_p50_out) { - # If p50 score present, also get peak regions file for this threshold. - if ($p50_sc) { - extract_peak_regions_from_scores($average_profile, $p50_peaks_bed_out, $max_merge_dist, $p50_sc); - } else { - qx/touch $p50_peaks_bed_out/; - } - } -} - -exit; - - - -################################################################################ -################################################################################ -# SUBROUTINES. -################################################################################ - - -sub array_mean { - - my $mean = sum(@_)/@_; - return sprintf("%.5f", $mean); - -} - - -################################################################################ - -sub extract_peak_regions_from_p_values { - - my ($average_profile, $peak_regions_bed_file, $max_merge_dist, $max_p) = @_; - - my $old_ref = "no"; - my $in = "N"; - my $ref_id; - my $start; - my $end; - my $best_p = 1; - my $best_sc = -1000; - my $region_s; - my $region_e; - my $zero_pos; - - my $temp_bed_file = "peak_regions.tmp.bed"; - - open (IN, $average_profile) or die "Cannot open $average_profile: $!"; - open (OUT, '>', $temp_bed_file) or die "Cannot open $temp_bed_file: $!"; - - while (<IN>) { - chomp; - my ($ref, $s, $sc, $p) = (split /\t/)[0,1,2,3]; - # If file has zero-based positions. - if ($s == 0) { - $zero_pos = 1; - } - # If positions are one-based, make them zero-based. - unless ($zero_pos) { - $s -= 1; - } - # At transcript ends, if in positive region, write and reset. - if ($old_ref ne $ref) { - if ($in eq "Y") { - print OUT "$ref_id\t$region_s\t$region_e\t$end;$best_sc;$best_p\t0\t+\n"; - $in = "N"; - } - } - $old_ref = $ref; - # Deal with good p-value regions. - if ($p <= $max_p) { - # Start of a positive cluster. - if ($in eq "N") { - $start = $s; - $region_s = $s; - $region_e = $s + 1; - $end = $s + 1; - $best_p = $p; - $best_sc = $sc; - $ref_id = $ref; - $in = "Y"; - next; - # Inside a positive cluster. - } elsif ($in eq "Y") { - if ($p < $best_p) { - $start = $s; - $end = $s + 1; - $best_p = $p; - $best_sc = $sc; - $ref_id = $ref; - } - $region_e++; - next; - } - } else { - # If we were in positive cluster before. - if ($in eq "Y") { - print OUT "$ref_id\t$region_s\t$region_e\t$end;$best_sc;$best_p\t0\t+\n"; - $in = "N"; - } - } - } - # After last line processed. - if ($in eq "Y") { - print OUT "$ref_id\t$region_s\t$region_e\t$end;$best_sc;$best_p\t0\t+\n"; - $in = "N"; - } - close IN; - close OUT; - # If merge distance zero (i.e. end of one block is -1 from start of next block). - if ($max_merge_dist == 0) { - qx/cat $temp_bed_file > $peak_regions_bed_file/; - } else { - # Merge nearby regions. - open(IN, $temp_bed_file) or die "Cannot open $temp_bed_file: $!"; - open(OUT, '>', $peak_regions_bed_file) or die "Cannot open $peak_regions_bed_file: $!"; - # For storing current block stats. - my $block_chr = 0; - my ($block_s, $block_e, $block_best_pos, $block_best_p, $block_best_sc); - while (<IN>) { - chomp; - my ($chr, $s, $e, $id) = (split /\t/)[0,1,2,3]; - my ($best_pos, $best_sc, $best_p) = (split /;/, $id); - if ($chr eq $block_chr) { - # If $block_e, $s within merge merge. - if ( ($s - $block_e) <= $max_merge_dist ) { - # Update block stats. - $block_e = $e; - if ($block_best_p > $best_p) { - $block_best_p = $best_p; - $block_best_sc = $best_sc; - $block_best_pos = $best_pos; - } - } else { - # If $e outside merge range, print block. - print OUT "$block_chr\t$block_s\t$block_e\t$block_best_pos;$block_best_sc;$block_best_p\t0\t+\n"; - # Store new block. - ($block_chr, $block_s, $block_e, $block_best_pos, $block_best_sc, $block_best_p) = ($chr, $s, $e, $best_pos, $best_sc, $best_p); - } - - } else { - # If new chromosome, print last block, otherwise it is the first block. - if ($block_chr) { - print OUT "$block_chr\t$block_s\t$block_e\t$block_best_pos;$block_best_sc;$block_best_p\t0\t+\n"; - } - ($block_chr, $block_s, $block_e, $block_best_pos, $block_best_sc, $block_best_p) = ($chr, $s, $e, $best_pos, $best_sc, $best_p); - } - } - # Print last block. - if ($block_chr) { - print OUT "$block_chr\t$block_s\t$block_e\t$block_best_pos;$block_best_sc;$block_best_p\t0\t+\n"; - } - close OUT; - close IN; - } - qx/rm -f $temp_bed_file/; -} - - -################################################################################ - -sub extract_peak_regions_from_scores { - - my ($average_profile, $peak_regions_bed_file, $max_merge_dist, $min_sc) = @_; - - my $old_ref = "no"; - my $in = "N"; - my $ref_id; - my $start; - my $end; - my $best_sc = -1000; - my $region_s; - my $region_e; - my $zero_pos; - - my $temp_bed_file = "peak_regions.tmp.bed"; - - open (IN, $average_profile) or die "Cannot open $average_profile: $!"; - open (OUT, '>', $temp_bed_file) or die "Cannot open $temp_bed_file: $!"; - - while (<IN>) { - chomp; - my ($ref, $s, $sc) = (split /\t/)[0,1,2]; - # If file has zero-based positions. - if ($s == 0) { - $zero_pos = 1; - } - # If positions are one-based, make them zero-based. - unless ($zero_pos) { - $s -= 1; - } - # At transcript ends, if in positive region, write and reset. - if ($old_ref ne $ref) { - if ($in eq "Y") { - print OUT "$ref_id\t$region_s\t$region_e\t$end;$best_sc\t0\t+\n"; - $in = "N"; - } - } - $old_ref = $ref; - # Deal with positive regions. - if ($sc > $min_sc) { - # Start of a positive cluster. - if ($in eq "N") { - $start = $s; - $region_s = $s; - $region_e = $s + 1; - $end = $s + 1; - $best_sc = $sc; - $ref_id = $ref; - $in = "Y"; - next; - # Inside a positive cluster. - } elsif ($in eq "Y") { - if ($sc > $best_sc) { - $start = $s; - $end = $s + 1; - $best_sc = $sc; - $ref_id = $ref; - } - $region_e++; - next; - } - } else { - # If we were in positive cluster before. - if ($in eq "Y") { - print OUT "$ref_id\t$region_s\t$region_e\t$end;$best_sc\t0\t+\n"; - $in = "N"; - } - } - } - # After last line processed. - if ($in eq "Y") { - print OUT "$ref_id\t$region_s\t$region_e\t$end;$best_sc\t0\t+\n"; - $in = "N"; - } - close IN; - close OUT; - # If merge distance zero (i.e. end of one block is -1 from start of next block). - if ($max_merge_dist == 0) { - qx/cat $temp_bed_file > $peak_regions_bed_file/; - } else { - # Merge nearby regions. - open(IN, $temp_bed_file) or die "Cannot open $temp_bed_file: $!"; - open(OUT, '>', $peak_regions_bed_file) or die "Cannot open $peak_regions_bed_file: $!"; - # For storing current block stats. - my $block_chr = 0; - my ($block_s, $block_e, $block_best_pos, $block_best_sc); - while (<IN>) { - chomp; - my ($chr, $s, $e, $id) = (split /\t/)[0,1,2,3]; - my ($best_pos, $best_sc) = (split /;/, $id); - if ($chr eq $block_chr) { - # If $block_e, $s within merge merge. - if ( ($s - $block_e) <= $max_merge_dist ) { - # Update block stats. - $block_e = $e; - if ($block_best_sc < $best_sc) { - $block_best_sc = $best_sc; - $block_best_pos = $best_pos; - } - } else { - # If $e outside merge range, print block. - print OUT "$block_chr\t$block_s\t$block_e\t$block_best_pos;$block_best_sc\t0\t+\n"; - # Store new block. - ($block_chr, $block_s, $block_e, $block_best_pos, $block_best_sc) = ($chr, $s, $e, $best_pos, $best_sc); - } - - } else { - # If new chromosome, print last block, otherwise it is the first block. - if ($block_chr) { - print OUT "$block_chr\t$block_s\t$block_e\t$block_best_pos;$block_best_sc\t0\t+\n"; - } - ($block_chr, $block_s, $block_e, $block_best_pos, $block_best_sc) = ($chr, $s, $e, $best_pos, $best_sc); - } - - } - # Print last block. - if ($block_chr) { - print OUT "$block_chr\t$block_s\t$block_e\t$block_best_pos;$block_best_sc\t0\t+\n"; - } - close OUT; - close IN; - } - qx/rm -f $temp_bed_file/; -} - - -################################################################################ - - -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/graphprot_predict_wrapper.py Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,298 @@ +#!/usr/bin/env python3 + +import subprocess +import argparse +import shutil +import gplib +import gzip +import sys +import os + + +""" + +TOOL DEPENDENCIES +================= + +GraphProt 1.1.7 +Best install via: +https://anaconda.org/bioconda/graphprot +Tested with: miniconda3, conda 4.7.12 + + +Script: What's my job this time, master? +Author: It'll be a though one. +Script: I take this as a given. +Author: Oh yeah? +Script: ... I'm ready. + + +OUTPUT FILES +============ + + data_id.avg_profile + data_id.avg_profile.peaks.bed +--conf-out + data_id.avg_profile.p50.peaks.bed +--gen-site-bed + data_id.avg_profile.genomic_peaks.bed +--conf-out --gen-site-bed + data_id.avg_profile.p50.genomic_peaks.bed +--ws-pred + data_id.predictions +--ws-pred --conf-out + data_id.predictions + data_id.p50.predictions + + +EXAMPLE CALLS +============= + +python graphprot_predict_wrapper.py --model test2.model --params test2.params --fasta gp_data/test10_predict.fa --data-id test2pred --gp-output +python graphprot_predict_wrapper.py --model test2.model --params test2.params --fasta gp_data/test10_predict.fa --data-id test2pred --gen-site-bed gp_data/test10_predict.bed +python graphprot_predict_wrapper.py --model test2.model --params test2.params --fasta gp_data/test10_predict.fa --data-id test2pred --gen-site-bed gp_data/test10_predict.bed --conf-out +python graphprot_predict_wrapper.py --model test2.model --params test2.params --fasta gp_data/test10_predict.fa --data-id test2pred --conf-out --ws-pred + +python graphprot_predict_wrapper.py --model test-data/test.model --params test-data/test.params --fasta test-data/test_predict.fa --data-id predtest + +python graphprot_predict_wrapper.py --model test-data/test.model --params test-data/test.params --fasta test-data/test_predict.fa --data-id predtest --gen-site-bed test-data/test_predict.bed --sc-thr 0.0 --max-merge-dist 0 --conf-out --ap-extlr 5 + +python graphprot_predict_wrapper.py --data-id GraphProt --fasta test-data/test_predict.fa --model test-data/test.model --params test-data/test.params --gen-site-bed test-data/test_predict.bed --sc-thr 0.0 --max-merge-dist 0 --conf-out --ap-extlr 5 + + +pwd && python '/home/uhlm/Dokumente/Projekte/GraphProt_galaxy_new/galaxytools/tools/rna_tools/graphprot/graphprot_predict_wrapper.py' --data-id GraphProt --fasta /tmp/tmpmuslpc1h/files/0/8/c/dataset_08c48d88-e3b5-423b-acf6-bf89b8c60660.dat --model /tmp/tmpmuslpc1h/files/e/6/4/dataset_e6471bb4-e74c-4372-bc49-656f900e7191.dat --params /tmp/tmpmuslpc1h/files/b/6/5/dataset_b65e8cf4-d3e6-429e-8d57-1d401adf4b3c.dat --gen-site-bed /tmp/tmpmuslpc1h/files/5/1/a/dataset_51a38b65-5943-472d-853e-5d845fa8ac3e.dat --sc-thr 0.0 --max-merge-dist 0 --conf-out --ap-extlr 5 + + +""" + +################################################################################ + +def setup_argument_parser(): + """Setup argparse parser.""" + help_description = """ + Galaxy wrapper script for GraphProt (-action predict and -action + predict_profile) to compute whole site or position-wise scores for input + FASTA sequences. + By default, profile predictions are calculated, followed by average + profiles computions and peak regions extraction from average profiles. + If --ws-pred is set, whole site score predictions on input sequences + will be run instead. + If --conf-out is set, sites or peak regions with a score >= the median + score of positive training sites will be output. + If --gen-site-bed .bed file is provided, peak regions will be output + with genomic coordinates too. + + """ + # Define argument parser. + p = argparse.ArgumentParser(add_help=False, + prog="graphprot_predict_wrapper.py", + description=help_description, + formatter_class=argparse.MetavarTypeHelpFormatter) + + # Argument groups. + p_man = p.add_argument_group("REQUIRED ARGUMENTS") + p_opt = p.add_argument_group("OPTIONAL ARGUMENTS") + + # Required arguments. + p_opt.add_argument("-h", "--help", + action="help", + help="Print help message") + p_man.add_argument("--fasta", + dest="in_fa", + type=str, + required = True, + help = "Sequences .fa file to predict on (option -fasta)") + p_man.add_argument("--model", + dest="in_model", + type=str, + required = True, + help = "GraphProt model file to use for predictions (option -model)") + p_man.add_argument("--params", + dest="in_params", + type=str, + required = True, + help = "Parameter file for given model") + p_man.add_argument("--data-id", + dest="data_id", + type=str, + required = True, + help = "Data ID (option -prefix)") + # ---> I'm a conditional argument <--- + p_opt.add_argument("--ws-pred", + dest = "ws_pred", + default = False, + action = "store_true", + help = "Run a whole site prediction instead of calculating profiles (default: false)") + # Additional arguments. + p_opt.add_argument("--sc-thr", + dest="score_thr", + type = float, + default = 0, + help = "Score threshold for extracting average profile peak regions (default: 0)") + p_opt.add_argument("--max-merge-dist", + dest="max_merge_dist", + type = int, + default = 0, + choices = [0,1,2,3,4,5,6,7,8,9,10], + help = "Maximum merge distance for nearby peak regions (default: report all non-overlapping regions)") + p_opt.add_argument("--gen-site-bed", + dest="genomic_sites_bed", + type=str, + help = ".bed file specifying the genomic regions of the input .fa sequences. Corrupt .bed information will be punished (default: false)") + p_opt.add_argument("--conf-out", + dest="conf_out", + default = False, + action = "store_true", + help = "Output filtered peak regions BED file or predictions file (if --ws-pred) using the median positive training site score for filtering (default: false)") + p_opt.add_argument("--gp-output", + dest = "gp_output", + default = False, + action = "store_true", + help = "Print output produced by GraphProt (default: false)") + p_opt.add_argument("--ap-extlr", + dest="ap_extlr", + type = int, + default = 5, + choices = [0,1,2,3,4,5,6,7,8,9,10], + help = "Define average profile up- and downstream extension to produce the average profile. The mean over small sequence windows (window length = --ap-extlr*2 + 1) is used to get position scores, thus the average profile is more smooth than the initial profile output by GraphProt (default: 5)") + return p + + +################################################################################ + +if __name__ == '__main__': + + # Setup argparse. + parser = setup_argument_parser() + # Read in command line arguments. + args = parser.parse_args() + + """ + Do all sorts of sanity checking. + + """ + # Check for Linux. + assert "linux" in sys.platform, "please use Linux" + # Check tool availability. + assert gplib.is_tool("GraphProt.pl"), "GraphProt.pl not in PATH" + # Check file inputs. + assert os.path.exists(args.in_fa), "input .fa file \"%s\" not found" %(args.in_fa) + assert os.path.exists(args.in_model), "input .model file \"%s\" not found" %(args.in_model) + assert os.path.exists(args.in_params), "input .params file \"%s\" not found" %(args.in_params) + # Count .fa entries. + c_in_fa = gplib.count_fasta_headers(args.in_fa) + assert c_in_fa, "input .fa file \"%s\" no headers found" %(args.in_fa) + print("# input .fa sequences: %i" %(c_in_fa)) + # Read in FASTA sequences to check for uppercase sequences. + seqs_dic = gplib.read_fasta_into_dic(args.in_fa) + c_uc_nt = gplib.seqs_dic_count_uc_nts(seqs_dic) + assert c_uc_nt, "no uppercase nucleotides in input .fa sequences. Please change sequences to uppercase (keep in mind GraphProt only scores uppercase regions (according to its viewpoint concept))" + if not args.ws_pred: + # Check for lowercase sequences. + c_lc_nt = gplib.seqs_dic_count_lc_nts(seqs_dic) + assert not c_lc_nt, "lowercase nucleotides not allowed in profile predictions, since GraphProt only scores uppercase regions (according to its viewpoint concept))" + # Check .bed. + if args.genomic_sites_bed: + # An array of checks, marvelous. + assert os.path.exists(args.genomic_sites_bed), "genomic .bed file \"%s\" not found" %(args.genomic_sites_bed) + # Check .bed for content. + assert gplib.count_file_rows(args.genomic_sites_bed), "genomic .bed file \"%s\" is empty" %(args.genomic_sites_bed) + # Check .bed for 6-column format. + assert gplib.bed_check_six_col_format(args.genomic_sites_bed), "genomic .bed file \"%s\" appears to not be in 6-column .bed format" %(args.genomic_sites_bed) + # Check for unique column 4 IDs. + assert gplib.bed_check_unique_ids(args.genomic_sites_bed), "genomic .bed file \"%s\" column 4 IDs not unique" %(args.genomic_sites_bed) + # Read in .bed regions, compare to FASTA sequences (compare IDs + lengths) + seq_len_dic = gplib.get_seq_lengths_from_seqs_dic(seqs_dic) + reg_len_dic = gplib.bed_get_region_lengths(args.genomic_sites_bed) + for seq_id in seq_len_dic: + seq_l = seq_len_dic[seq_id] + assert seq_id in reg_len_dic, "sequence ID \"\" missing in input .bed \"\"" %(seq_id, args.genomic_sites_bed) + reg_l = reg_len_dic[seq_id] + assert seq_l == reg_l, "sequence length differs from .bed region length (%i != %i)" %(seq_l, reg_l) + # Read in model parameters. + param_dic = gplib.graphprot_get_param_dic(args.in_params) + # Create GraphProt parameter string. + param_string = gplib.graphprot_get_param_string(args.in_params) + + """ + Run predictions. + + """ + if args.ws_pred: + # Do whole site prediction. + print("Starting whole site predictions on input .fa file (-action predict) ... ") + check_cmd = "GraphProt.pl -action predict -prefix " + args.data_id + " -fasta " + args.in_fa + " " + param_string + " -model " + args.in_model + output = subprocess.getoutput(check_cmd) + assert output, "the following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + if args.gp_output: + print(output) + ws_predictions_file = args.data_id + ".predictions" + assert os.path.exists(ws_predictions_file), "Whole site prediction output .predictions file \"%s\" not found" %(ws_predictions_file) + if args.conf_out: + # Filter by pos_train_ws_pred_median median. + assert "pos_train_ws_pred_median" in param_dic, "whole site top scores median information missing in .params file" + pos_train_ws_pred_median = float(param_dic["pos_train_ws_pred_median"]) + # Filtered file. + filt_ws_predictions_file = args.data_id + ".p50.predictions" + print("Extracting p50 sites from whole site predictions (score threshold = %f) ... " %(pos_train_ws_pred_median)) + gplib.graphprot_filter_predictions_file(ws_predictions_file, filt_ws_predictions_file, + sc_thr=pos_train_ws_pred_median) + else: + # Do profile prediction. + print("Starting profile predictions on on input .fa file (-action predict_profile) ... ") + check_cmd = "GraphProt.pl -action predict_profile -prefix " + args.data_id + " -fasta " + args.in_fa + " " + param_string + " -model " + args.in_model + output = subprocess.getoutput(check_cmd) + assert output, "the following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + if args.gp_output: + print(output) + profile_predictions_file = args.data_id + ".profile" + assert os.path.exists(profile_predictions_file), "Profile prediction output .profile file \"%s\" not found" %(profile_predictions_file) + + # Profile prediction output files. + avg_prof_file = args.data_id + ".avg_profile" + avg_prof_peaks_file = args.data_id + ".avg_profile.peaks.bed" + avg_prof_gen_peaks_file = args.data_id + ".avg_profile.genomic_peaks.bed" + avg_prof_peaks_p50_file = args.data_id + ".avg_profile.p50.peaks.bed" + avg_prof_gen_peaks_p50_file = args.data_id + ".avg_profile.p50.genomic_peaks.bed" + + # Get sequence IDs in order from input .fa file. + seq_ids_list = gplib.fasta_read_in_ids(args.in_fa) + # Calculate average profiles. + print("Getting average profile from profile (extlr for smoothing: %i) ... " %(args.ap_extlr)) + gplib.graphprot_profile_calculate_avg_profile(profile_predictions_file, + avg_prof_file, + ap_extlr=args.ap_extlr, + seq_ids_list=seq_ids_list, + method=2) + # Extract peak regions on sequences with threshold score 0. + print("Extracting peak regions from average profile (score threshold = 0) ... ") + gplib.graphprot_profile_extract_peak_regions(avg_prof_file, avg_prof_peaks_file, + max_merge_dist=args.max_merge_dist, + sc_thr=args.score_thr) + # Convert peaks to genomic coordinates. + if args.genomic_sites_bed: + print("Converting peak regions to genomic coordinates ... ") + gplib.bed_peaks_to_genomic_peaks(avg_prof_peaks_file, avg_prof_gen_peaks_file, + print_rows=False, + genomic_sites_bed=args.genomic_sites_bed) + # gplib.make_file_copy(avg_prof_gen_peaks_file, avg_prof_peaks_file) + # Extract peak regions with threshold score p50. + if args.conf_out: + sc_id = "pos_train_avg_profile_median_%i" %(args.ap_extlr) + # Filter by pos_train_ws_pred_median median. + assert sc_id in param_dic, "average profile extlr %i median information missing in .params file" %(args.ap_extlr) + p50_sc_thr = float(param_dic[sc_id]) + print("Extracting p50 peak regions from average profile (score threshold = %f) ... " %(p50_sc_thr)) + gplib.graphprot_profile_extract_peak_regions(avg_prof_file, avg_prof_peaks_p50_file, + max_merge_dist=args.max_merge_dist, + sc_thr=p50_sc_thr) + # Convert peaks to genomic coordinates. + if args.genomic_sites_bed: + print("Converting p50 peak regions to genomic coordinates ... ") + gplib.bed_peaks_to_genomic_peaks(avg_prof_peaks_p50_file, avg_prof_gen_peaks_p50_file, + genomic_sites_bed=args.genomic_sites_bed) + # Done. + print("Script: I'm done.") + print("Author: ... ") + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/graphprot_train_predict.xml Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,280 @@ +<tool id="graphprot_predict_profile" name="GraphProt" version="1.1.7+galaxy1"> + <description>- Train models and predict RBP binding profiles</description> + <requirements> + <requirement type="package" version="1.1.7">graphprot</requirement> + </requirements> + + <command detect_errors="exit_code"><![CDATA[ + #if $action_type.action_type_selector == 'train': + python '$__tool_directory__/graphprot_train_wrapper.py' + --data-id GraphProt + --pos '$action_type.pos_fasta_file' + --neg '$action_type.neg_fasta_file' + $action_type.train_str_model + #if $action_type.hpo_options.hpo_mode_type.hpo_mode_type_selector == 'take': + --opt-set-size $action_type.hpo_options.hpo_mode_type.opt_set_size + #elif $action_type.hpo_options.hpo_mode_type.hpo_mode_type_selector == 'supply': + --opt-pos '$action_type.hpo_options.hpo_mode_type.pos_parop_fasta' + --opt-neg '$action_type.hpo_options.hpo_mode_type.neg_parop_fasta' + #end if + $action_type.training_options.disable_cv + $action_type.training_options.disable_motifs + --min-train $action_type.training_options.min_train + + #elif $action_type.action_type_selector == 'predict': + python '$__tool_directory__/graphprot_predict_wrapper.py' + --data-id GraphProt + --fasta '$action_type.input_fasta_file' + --model '$action_type.model_file' + --params $action_type.params_file + #if $action_type.genomic_sites_bed_file: + --gen-site-bed '$action_type.genomic_sites_bed_file' + #end if + --sc-thr $action_type.prediction_options.score_thr + --max-merge-dist $action_type.prediction_options.max_merge_dist + --ap-extlr $action_type.prediction_options.ap_extlr + $action_type.prediction_options.conf_out + $action_type.prediction_options.ws_pred_out + #end if + + + ]]></command> + + <inputs> + <conditional name="action_type"> + + <param name="action_type_selector" type="select" label="Select an action"> + <option value="train" selected="true">Train a model</option> + <option value="predict">Predict on input sequences</option> + </param> + + <when value="train"> + <param name="pos_fasta_file" type="data" format="fasta" + label="Positive sequences FASTA file" argument="-fasta" + help="Positive sequences (== RBP binding sites) FASTA file for model training"/> + <param name="neg_fasta_file" type="data" format="fasta" + label="Negative sequences FASTA file" argument="-negfasta" + help="Negative sequences FASTA file for model training"/> + <param name="train_str_model" label="Train a structure model" type="boolean" + truevalue="--str-model" falsevalue="" checked="False" + help="Train a structure model (default: train a sequence model)"/> + + <section name="hpo_options" title="Hyperparameter optimization settings"> + + <conditional name="hpo_mode_type"> + <param name="hpo_mode_type_selector" type="select" label="Select strategy"> + <option value="take" selected="true">Take sequences for optimization from input</option> + <option value="supply">Supply sequences for optimization</option> + </param> + <when value="take"> + <param name="opt_set_size" type="integer" value="500" + label="Number of sequences for hyperparameter optimization" + help="Hyperparameter optimization set size (taken away from both positive and negative input sequences) (default: 500)"/> + </when> + <when value="supply"> + <param name="pos_parop_fasta" type="data" format="fasta" + label="Positive sequences FASTA file" + help="Positive (== RBP binding sites) sequences FASTA file for hyperparameter optimization"/> + <param name="neg_parop_fasta" type="data" format="fasta" + label="Negative sequences FASTA file" + help="Negative sequences FASTA file for hyperparameter optimization"/> + </when> + </conditional> + </section> + + <section name="training_options" title="Training options"> + <param name="disable_cv" label="Disable 10-fold cross validation" type="boolean" + truevalue="--disable-cv" falsevalue="" checked="False" + help="Disable 10-fold cross validation step. As a result, no generalization performance results (.cv_results) are output. On the other hand, run time is reduced considerably (default: false)"/> + <param name="disable_motifs" label="Disable motif generation" type="boolean" + truevalue="--disable-motifs" falsevalue="" checked="False" + help="Disable motif generation step, therefore no _motif and _motif.png files are output (default: false)"/> + <param name="min_train" type="integer" value="750" + label="Minimum number of training sites demanded" + help="Minimum number of training sites demanded (for both negatives and positives). In general, try to get more training sites if possible (>> 1000), before lowering this number (default: 750)"/> + </section> + </when> + <when value="predict"> + + <param name="input_fasta_file" type="data" format="fasta" + label="Input FASTA file" argument="-fasta" + help="FASTA file with sequences for which to predict binding profiles or whole site scores"/> + <param name="model_file" type="data" format="data" + label="GraphProt model file" argument="-model" + help="GraphProt model to use for predictions"/> + <param name="params_file" type="data" format="txt" + label="Model parameter file" argument="-params" + help="Parameter file containing model parameters"/> + <param name="genomic_sites_bed_file" type="data" format="bed" optional="True" + label="Genomic BED file with coordinates from input sequences" + help="BED file specifying the genomic regions of the input sequences, to also output peak regions with their genomic coordinates (default: false)"/> + + <section name="prediction_options" title="Prediction options"> + <param name="score_thr" type="float" value="0" + label="Set GraphProt average profile peak score threshold for reporting peak regions" + help="Regions with peak score higher or equal the given value are reported (default: 0)"/> + + <param name="ap_extlr" type="integer" value="5" min="0" max="10" + label="Smoothing parameter for calculating the average profile" + help="Defines the average profile up- and downstream extension to produce the average profile. The mean over small sequence windows (window_length = set_value*2 + 1) is used to get the average profile position-wise scores. A value of 0 means no additional smoothing (== original profile scores), while 10 is applies fairly strong smoothing (default: 5)"/> + + <param name="max_merge_dist" type="integer" value="0" min="0" max="10" + label="Maximum distance between two peak regions for merging" argument="-merge-dist" + help="By default all non-overlapping regions will be reported. E.g. a distance of 1 means that two regions above the set threshold score will be merged if there is 1 nucleotide that separates the two regions"/> + + <param name="ws_pred_out" label="Predict whole site instead of profile scores" type="boolean" + truevalue="--ws-pred" falsevalue="" checked="False" + help="Run a whole site prediction instead of calculating profiles (default: false)"/> + <param name="conf_out" label="Output high-confidence (p50) peak regions" type="boolean" + truevalue="--conf-out" falsevalue="" checked="False" + help="Output filtered peak regions BED file or predictions file (if whole site scores prediction enabled), using the median positive training site score (stored in .params file) for filtering (default: false)"/> + </section> + </when> + </conditional> + </inputs> + + <outputs> + <data name="model_out_file" format="txt" from_work_dir="GraphProt.model" label="${tool.name} on ${on_string}: GraphProt model file"> + <filter>action_type["action_type_selector"] == "train"</filter> + </data> + + <data name="params_out_file" format="txt" from_work_dir="GraphProt.params" label="${tool.name} on ${on_string}: GraphProt model parameters file"> + <filter>action_type["action_type_selector"] == "train"</filter> + </data> + + <data name="cv_results_out_file" format="txt" from_work_dir="GraphProt.cv_results" label="${tool.name} on ${on_string}: GraphProt cross validation results file"> + <filter>action_type["action_type_selector"] == "train" and not action_type["training_options"]["disable_cv"]</filter> + </data> + + <data name="seq_motif_out_file" format="txt" from_work_dir="GraphProt.sequence_motif" label="${tool.name} on ${on_string}: GraphProt sequence motif text file"> + <filter>action_type["action_type_selector"] == "train" and not action_type["training_options"]["disable_motifs"]</filter> + </data> + <data name="seq_motif_png_out_file" format="png" from_work_dir="GraphProt.sequence_motif.png" label="${tool.name} on ${on_string}: GraphProt sequence motif png file"> + <filter>action_type["action_type_selector"] == "train" and not action_type["training_options"]["disable_motifs"]</filter> + </data> + + <data name="str_motif_out_file" format="txt" from_work_dir="GraphProt.structure_motif" label="${tool.name} on ${on_string}: GraphProt structure motif text file"> + <filter>action_type["action_type_selector"] == "train" and not action_type["training_options"]["disable_motifs"]</filter> + </data> + + <data name="str_motif_png_out_file" format="png" from_work_dir="GraphProt.structure_motif.png" label="${tool.name} on ${on_string}: GraphProt structure motif png file"> + <filter>action_type["action_type_selector"] == "train" and not action_type["training_options"]["disable_motifs"] and action_type["train_str_model"]</filter> + </data> + + <data name="avg_profile_out_file" format="txt" from_work_dir="GraphProt.avg_profile" label="${tool.name} on ${on_string}: GraphProt average profile file"> + <filter>action_type["action_type_selector"] == "predict" and not action_type["prediction_options"]["ws_pred_out"]</filter> + </data> + + <data name="peaks_out_file" format="bed" from_work_dir="GraphProt.avg_profile.peaks.bed" label="${tool.name} on ${on_string}: GraphProt average profile peaks BED file"> + <filter>action_type["action_type_selector"] == "predict" and not action_type["prediction_options"]["ws_pred_out"]</filter> + </data> + + <data name="p50_peaks_out_file" format="bed" from_work_dir="GraphProt.avg_profile.p50.peaks.bed" label="${tool.name} on ${on_string}: GraphProt average profile p50 peaks BED file"> + <filter>action_type["action_type_selector"] == "predict" and action_type["prediction_options"]["conf_out"] and not action_type["prediction_options"]["ws_pred_out"]</filter> + </data> + + <data name="genomic_peaks_out_file" format="bed" from_work_dir="GraphProt.avg_profile.genomic_peaks.bed" label="${tool.name} on ${on_string}: GraphProt average profile genomic peaks BED file"> + <filter>action_type["action_type_selector"] == "predict" and action_type["genomic_sites_bed_file"] and not action_type["prediction_options"]["ws_pred_out"]</filter> + </data> + + <data name="genomic_p50_peaks_out_file" format="bed" from_work_dir="GraphProt.avg_profile.p50.genomic_peaks.bed" label="${tool.name} on ${on_string}: GraphProt average profile p50 genomic peaks BED file"> + <filter>action_type["action_type_selector"] == "predict" and action_type["prediction_options"]["conf_out"] and action_type["genomic_sites_bed_file"] and not action_type["prediction_options"]["ws_pred_out"]</filter> + </data> + + <data name="predictions_out_file" format="txt" from_work_dir="GraphProt.predictions" label="${tool.name} on ${on_string}: GraphProt whole site predictions file"> + <filter>action_type["action_type_selector"] == "predict" and action_type["prediction_options"]["ws_pred_out"]</filter> + </data> + + <data name="p50_predictions_out_file" format="txt" from_work_dir="GraphProt.p50.predictions" label="${tool.name} on ${on_string}: GraphProt whole site p50 predictions file"> + <filter>action_type["action_type_selector"] == "predict" and action_type["prediction_options"]["ws_pred_out"] and action_type["prediction_options"]["conf_out"]</filter> + </data> + + </outputs> + + <tests> + + <test expect_num_outputs="5"> + <param name="action_type_selector" value="train"/> + <param name="pos_fasta_file" value="test_positives.train.fa" ftype="fasta"/> + <param name="neg_fasta_file" value="test_negatives.train.fa" ftype="fasta"/> + <param name="hpo_mode_type_selector" value="supply"/> + <param name="pos_parop_fasta" value="test_positives.parop.fa" ftype="fasta"/> + <param name="neg_parop_fasta" value="test_negatives.parop.fa" ftype="fasta"/> + <param name="disable_cv" value="True"/> + <param name="disable_motifs" value="False"/> + <param name="min_train" value="500"/> + <output name="model_out_file" file="test.model"/> + <output name="params_out_file" file="test.params"/> + <output name="seq_motif_out_file" file="test.sequence_motif"/> + </test> + + <test expect_num_outputs="5"> + <param name="action_type_selector" value="predict"/> + <param name="input_fasta_file" value="test_predict.fa" ftype="fasta"/> + <param name="model_file" value="test.model" ftype="txt"/> + <param name="params_file" value="test.params" ftype="txt"/> + <param name="genomic_sites_bed_file" value="test_predict.bed" ftype="bed"/> + <param name="conf_out" value="True"/> + <output name="genomic_peaks_out_file" file="test_predict.avg_profile.genomic_peaks.bed"/> + <output name="avg_profile_out_file" file="test_predict.avg_profile"/> + <output name="peaks_out_file" file="test_predict.avg_profile.peaks.bed"/> + <output name="p50_peaks_out_file" file="test_predict.avg_profile.p50.peaks.bed"/> + <output name="genomic_p50_peaks_out_file" file="test_predict.avg_profile.p50.genomic_peaks.bed"/> + </test> + + <test expect_num_outputs="2"> + <param name="action_type_selector" value="predict"/> + <param name="input_fasta_file" value="test_predict.fa" ftype="fasta"/> + <param name="model_file" value="test.model" ftype="txt"/> + <param name="params_file" value="test.params" ftype="txt"/> + <param name="ws_pred_out" value="True"/> + <param name="conf_out" value="True"/> + <output name="predictions_out_file" file="test_predict.predictions"/> + <output name="p50_predictions_out_file" file="test_predict.p50.predictions"/> + </test> + + </tests> + <help> + +Use GraphProt to train a model or to predict RBP binding profiles using a pretrained RBP model. + + +**Model training** + +To train a GraphProt model, a FASTA file with positive sequences (= RBP binding sites, usually determined by CLIP-seq) and a FASTA file with negative sequences (non-binding, e.g. randomly selected genomic sites) needs to be supplied. By default a sequence model is trained, since they often show similar performance compared to structure models while taking considerably less time to train. For hyperparameter optimization, a portion of the input FASTA sequences (usually n = 500) is taken away, but you can also provide separate optimization sets. After hyperparameter optimization, a model is trained using the input training sequences (minus the optimization set if not specified otherwise) with the determined optimized parameters. After that, a 10-fold cross validation is run on the training sequences to estimate the generalization performance of the model. Sequence and structure motifs (if structure model training enabled) are also output. Both cross validation and motif output can be disabled to further decrease the runtime. + +By default, the model training output files are: + +1) a .model file storing the model parameters + +2) a .params file storing model hyperparameters and additional information + +3) a .cv_results file containing the cross validation results + +4) _motif and motif.png files (sequence and / or structure) + + +**Profile prediction** + +This mode computes whole site or position-wise (= profile) binding scores for a given set input FASTA sequences. + +By default, binding profiles are calculated, followed by average profile computation and extraction of peak regions from the average profiles. The average binding profile is more smooth regarding the position-wise (per nucleotide) scores than the initial profile GraphProt outputs and is the recommended way to extract peaks. Note that the amount of smoothness can be controlled in the prediction options (with the lowest value 0 equaling the initial profile). A peak is defined as a contiguous region in the average profile with scores >= the set score threshold (by default 0, can be changed). In addition, a set of high confidence peak regions (p50) can be output. Here the threshold gets set to the median of the scores obtained from the positive training set during model training (information stored in parameters file). Moreover, the peak regions can be converted to genomic regions, if the genomic regions for the input FASTA sequences are supplied. + +Apart from predicting binding profiles, whole site predictions can be output as well. Here the output files are the scores for each input sequence, and optionally the p50 filtered set just like with the average profile peaks. + + +Summing up, the profile predictions output files are: + +1) an avg_profile file containing the position-wise (per nucleotide) binding profile scores + +2) one or several BED files containing the peak regions (all peaks, p50 peaks, all genomic peaks, p50 genomic peaks) + +3) if whole site prediction is enabled, a .predictions file and optionally a .p50.predictions file + + </help> + <citations> + <citation type="doi">10.1186/gb-2014-15-1-r17</citation> + </citations> +</tool> + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/graphprot_train_wrapper.py Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,431 @@ +#!/usr/bin/env python3 + +import subprocess +import argparse +import shutil +import gplib +import gzip +import sys +import os + + +""" + +TOOL DEPENDENCIES +================= + +GraphProt 1.1.7 +Best install via: +https://anaconda.org/bioconda/graphprot +Tested with: miniconda3, conda 4.7.12 + + +OUTPUT FILES +============ + + data_id.model + data_id.params +if not --disable-cv: + data_id.cv_results +if not --disable-motifs: + data_id.sequence_motif + data_id.sequence_motif.png + if --str-model: + data_id.structure_motif + data_id.structure_motif.png +Temporary: + data_id.predictions + data_id.profile + + + --opt-set-size int Hyperparameter optimization set size (taken away from both --pos and --neg) (default: 500) + --opt-pos str Positive (= binding site) sequences .fa file for hyperparameter optimization (default: take + --opt-set-size from --pos) + --opt-neg str Negative sequences .fa file for hyperparameter optimization (default: take --opt-set-size + from --neg) + --min-train int Minimum amount of training sites demanded (default: 500) + --disable-cv Disable cross validation step (default: false) + --disable-motifs Disable motif generation step (default: false) + --gp-output Print output produced by GraphProt (default: false) + --str-model Train a structure model (default: train a sequence model) + + +EXAMPLE CALLS +============= + +python graphprot_train_wrapper.py --pos gp_data/SERBP1_positives.train.fa --neg gp_data/SERBP1_negatives.train.fa --data-id test2 --disable-cv --gp-output --opt-set-size 200 --min-train 400 + +python graphprot_train_wrapper.py --pos gp_data/SERBP1_positives.train.fa --neg gp_data/SERBP1_negatives.train.fa --data-id test2 --disable-cv --opt-set-size 100 --min-train 200 + +python graphprot_train_wrapper.py --pos test-data/test_positives.train.fa --neg test-data/test_negatives.train.fa --data-id gptest2 --disable-cv --opt-pos test-data/test_positives.parop.fa --opt-neg test-data/test_negatives.parop.fa + +python graphprot_train_wrapper.py --pos test-data/test_positives.train.fa --neg test-data/test_negatives.train.fa --data-id gptest2 --disable-cv --disable-motifs --opt-pos test-data/test_positives.parop.fa --opt-neg test-data/test_negatives.parop.fa + + +""" + +################################################################################ + +def setup_argument_parser(): + """Setup argparse parser.""" + help_description = """ + Galaxy wrapper script for GraphProt to train a GraphProt model on + a given set of input sequences (positives and negatives .fa). By + default a sequence model is trained (due to structure models + being much slower to train). Also by default take a portion of + the input sequences for hyperparameter optimization (HPO) prior to + model training, and run a 10-fold cross validation and motif + generation after model training. Thus the following output + files are produced: + .model model file, .params model parameter file, .png motif files + (sequence, or sequence+structure), .cv_results CV results file. + After model training, predict on positives to get highest whole + site and profile scores found in binding sites. Take the median + score out of these to store in .params file, using it later + for outputting binding sites or peaks with higher confidence. + + """ + # Define argument parser. + p = argparse.ArgumentParser(add_help=False, + prog="graphprot_train_wrapper.py", + description=help_description, + formatter_class=argparse.MetavarTypeHelpFormatter) + + # Argument groups. + p_man = p.add_argument_group("REQUIRED ARGUMENTS") + p_opt = p.add_argument_group("OPTIONAL ARGUMENTS") + + # Required arguments. + p_opt.add_argument("-h", "--help", + action="help", + help="Print help message") + p_man.add_argument("--pos", + dest="in_pos_fa", + type=str, + required = True, + help = "Positive (= binding site) sequences .fa file for model training (option -fasta)") + p_man.add_argument("--neg", + dest="in_neg_fa", + type=str, + required = True, + help = "Negative sequences .fa file for model training (option -negfasta)") + p_man.add_argument("--data-id", + dest="data_id", + type=str, + required = True, + help = "Data ID (option -prefix)") + # Additional arguments. + p_opt.add_argument("--opt-set-size", + dest="opt_set_size", + type = int, + default = 500, + help = "Hyperparameter optimization set size (taken away from both --pos and --neg) (default: 500)") + p_opt.add_argument("--opt-pos", + dest="opt_pos_fa", + type=str, + help = "Positive (= binding site) sequences .fa file for hyperparameter optimization (default: take --opt-set-size from --pos)") + p_opt.add_argument("--opt-neg", + dest="opt_neg_fa", + type=str, + help = "Negative sequences .fa file for hyperparameter optimization (default: take --opt-set-size from --neg)") + p_opt.add_argument("--min-train", + dest="min_train", + type = int, + default = 500, + help = "Minimum amount of training sites demanded (default: 500)") + p_opt.add_argument("--disable-cv", + dest = "disable_cv", + default = False, + action = "store_true", + help = "Disable cross validation step (default: false)") + p_opt.add_argument("--disable-motifs", + dest = "disable_motifs", + default = False, + action = "store_true", + help = "Disable motif generation step (default: false)") + p_opt.add_argument("--gp-output", + dest = "gp_output", + default = False, + action = "store_true", + help = "Print output produced by GraphProt (default: false)") + p_opt.add_argument("--str-model", + dest = "train_str_model", + default = False, + action = "store_true", + help = "Train a structure model (default: train a sequence model)") + return p + + +################################################################################ + +if __name__ == '__main__': + + # Setup argparse. + parser = setup_argument_parser() + # Read in command line arguments. + args = parser.parse_args() + + """ + Do all sorts of sanity checking. + + """ + # Check for Linux. + assert "linux" in sys.platform, "please use Linux" + # Check tool availability. + assert gplib.is_tool("GraphProt.pl"), "GraphProt.pl not in PATH" + # Check file inputs. + assert os.path.exists(args.in_pos_fa), "positives .fa file \"%s\" not found" %(args.in_pos_fa) + assert os.path.exists(args.in_neg_fa), "negatives .fa file \"%s\" not found" %(args.in_neg_fa) + # Count .fa entries. + c_pos_fa = gplib.count_fasta_headers(args.in_pos_fa) + c_neg_fa = gplib.count_fasta_headers(args.in_neg_fa) + assert c_pos_fa, "positives .fa file \"%s\" no headers found" %(args.in_pos_fa) + assert c_neg_fa, "negatives .fa file \"%s\" no headers found" %(args.in_neg_fa) + print("# positive .fa sequences: %i" %(c_pos_fa)) + print("# negative .fa sequences: %i" %(c_neg_fa)) + # Check additional files. + if args.opt_pos_fa: + assert args.opt_neg_fa, "--opt-pos but no --opt-neg given" + if args.opt_neg_fa: + assert args.opt_pos_fa, "--opt-neg but no --opt-pos given" + # If parop .fa files given. + if args.opt_pos_fa and args.opt_neg_fa: + c_parop_pos_fa = gplib.count_fasta_headers(args.opt_pos_fa) + c_parop_neg_fa = gplib.count_fasta_headers(args.opt_neg_fa) + assert c_parop_pos_fa, "--opt-pos .fa file \"%s\" no headers found" %(args.opt_pos_fa) + assert c_parop_neg_fa, "--opt-neg .fa file \"%s\" no headers found" %(args.opt_neg_fa) + # Less than 500 for training?? You gotta be kidding. + assert c_pos_fa >= args.min_train, "--pos for training < %i, please provide more (try at least > 1000, the more the better)" %(args.min_train) + assert c_neg_fa >= args.min_train, "--neg for training < %i, please provide more (try at least > 1000, the more the better)" %(args.min_train) + # Looking closer at ratios. + pos_neg_ratio = c_parop_pos_fa / c_parop_neg_fa + if pos_neg_ratio < 0.8 or pos_neg_ratio > 1.25: + assert 0, "ratio of --opt-pos to --opt-neg < 0.8 or > 1.25 (ratio = %f). Try to keep ratio closer to 1 or better use identical numbers (keep in mind that performance measures such as accuracy or AUROC are not suitable for imbalanced datasets!)" %(pos_neg_ratio) + else: + # Define some minimum amount of training sites for the sake of sanity. + c_pos_train = c_pos_fa - args.opt_set_size + c_neg_train = c_neg_fa - args.opt_set_size + # Start complaining. + assert c_pos_fa >= args.opt_set_size, "# positives < --opt-set-size (%i < %i)" %(c_pos_fa, args.opt_set_size) + assert c_neg_fa >= args.opt_set_size, "# negatives < --opt-set-size (%i < %i)" %(c_neg_fa, args.opt_set_size) + assert c_pos_train >= args.opt_set_size, "# positives remaining for training < --opt-set-size (%i < %i)" %(c_pos_train, args.opt_set_size) + assert c_neg_train >= args.opt_set_size, "# negatives remaining for training < --opt-set-size (%i < %i)" %(c_neg_train, args.opt_set_size) + # Less than 500?? You gotta be kidding. + assert c_pos_train >= args.min_train, "# positives remaining for training < %i, please provide more (try at least > 1000, the more the better)" %(args.min_train) + assert c_neg_train >= args.min_train, "# negatives remaining for training < %i, please provide more (try at least > 1000, the more the better)" %(args.min_train) + # Looking closer at ratios. + pos_neg_ratio = c_pos_train / c_neg_train + if pos_neg_ratio < 0.8 or pos_neg_ratio > 1.25: + assert 0, "ratio of --pos to --neg < 0.8 or > 1.25 (ratio = %f). Try to keep ratio closer to 1 or better use identical numbers (keep in mind that performance measures such as accuracy or AUROC are not suitable for imbalanced datasets!)" %(pos_neg_ratio) + + """ + Generate parop + train .fa output files for hyperparameter optimization + training. + + """ + # Output files for training. + pos_parop_fa = args.data_id + ".positives.parop.fa" + neg_parop_fa = args.data_id + ".negatives.parop.fa" + pos_train_fa = args.data_id + ".positives.train.fa" + neg_train_fa = args.data_id + ".negatives.train.fa" + + # If parop .fa files given. + if args.opt_pos_fa and args.opt_neg_fa: + # Just copy parop and train files. + gplib.make_file_copy(args.opt_pos_fa, pos_parop_fa) + gplib.make_file_copy(args.opt_neg_fa, neg_parop_fa) + gplib.make_file_copy(args.in_pos_fa, pos_train_fa) + gplib.make_file_copy(args.in_neg_fa, neg_train_fa) + else: + # Generate parop + train .fa files from input .fa files. + gplib.split_fasta_into_test_train_files(args.in_pos_fa, pos_parop_fa, pos_train_fa, + test_size=args.opt_set_size) + gplib.split_fasta_into_test_train_files(args.in_neg_fa, neg_parop_fa, neg_train_fa, + test_size=args.opt_set_size) + + """ + Do the hyperparameter optimization. + + """ + print("Starting hyperparameter optimization (-action ls) ... ") + check_cmd = "GraphProt.pl -action ls -prefix " + args.data_id + " -fasta " + pos_parop_fa + " -negfasta " + neg_parop_fa + # If sequence model should be trained (default). + if not args.train_str_model: + check_cmd += " -onlyseq" + print(check_cmd) + output = subprocess.getoutput(check_cmd) + #assert output, "The following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + #if args.gp_output: + # print(output) + params_file = args.data_id + ".params" + assert os.path.exists(params_file), "Hyperparameter optimization output .params file \"%s\" not found" %(params_file) + # Add model type to params file. + if args.train_str_model: + gplib.echo_add_to_file("model_type: structure", params_file) + else: + gplib.echo_add_to_file("model_type: sequence", params_file) + # Get parameter string. + param_string = gplib.graphprot_get_param_string(params_file) + + """ + Do the model training. (Yowza!) + + """ + print("Starting model training (-action train) ... ") + check_cmd = "GraphProt.pl -action train -prefix " + args.data_id + " -fasta " + pos_train_fa + " -negfasta " + neg_train_fa + " " + param_string + print(check_cmd) + output = subprocess.getoutput(check_cmd) + assert output, "The following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + if args.gp_output: + print(output) + model_file = args.data_id + ".model" + assert os.path.exists(model_file), "Training output .model file \"%s\" not found" %(model_file) + + """ + Do the 10-fold cross validation. + + """ + if not args.disable_cv: + print("Starting 10-fold cross validation (-action cv) ... ") + check_cmd = "GraphProt.pl -action cv -prefix " + args.data_id + " -fasta " + pos_train_fa + " -negfasta " + neg_train_fa + " " + param_string + " -model " + model_file + print(check_cmd) + output = subprocess.getoutput(check_cmd) + assert output, "The following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + if args.gp_output: + print(output) + cv_results_file = args.data_id + ".cv_results" + assert os.path.exists(cv_results_file), "CV output .cv_results file \"%s\" not found" %(cv_results_file) + + """ + Do the motif generation. + + """ + if not args.disable_motifs: + print("Starting motif generation (-action motif) ... ") + check_cmd = "GraphProt.pl -action motif -prefix " + args.data_id + " -fasta " + pos_train_fa + " -negfasta " + neg_train_fa + " " + param_string + " -model " + model_file + print(check_cmd) + output = subprocess.getoutput(check_cmd) + assert output, "The following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + if args.gp_output: + print(output) + seq_motif_file = args.data_id + ".sequence_motif" + seq_motif_png_file = args.data_id + ".sequence_motif.png" + assert os.path.exists(seq_motif_file), "Motif output .sequence_motif file \"%s\" not found" %(seq_motif_file) + assert os.path.exists(seq_motif_png_file), "Motif output .sequence_motif.png file \"%s\" not found" %(seq_motif_png_file) + if args.train_str_model: + str_motif_file = args.data_id + ".structure_motif" + str_motif_png_file = args.data_id + ".structure_motif.png" + assert os.path.exists(str_motif_file), "Motif output .structure_motif file \"%s\" not found" %(str_motif_file) + assert os.path.exists(str_motif_png_file), "Motif output .structure_motif.png file \"%s\" not found" %(str_motif_png_file) + + """ + Do whole site predictions on positive training set. + + """ + print("Starting whole site predictions on positive training set (-action predict) ... ") + check_cmd = "GraphProt.pl -action predict -prefix " + args.data_id + " -fasta " + pos_train_fa + " " + param_string + " -model " + model_file + print(check_cmd) + output = subprocess.getoutput(check_cmd) + assert output, "The following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + if args.gp_output: + print(output) + ws_predictions_file = args.data_id + ".predictions" + assert os.path.exists(ws_predictions_file), "Whole site prediction output .predictions file \"%s\" not found" %(ws_predictions_file) + + """ + Do profile predictions on positive training set. + + """ + print("Starting profile predictions on positive training set (-action predict_profile) ... ") + check_cmd = "GraphProt.pl -action predict_profile -prefix " + args.data_id + " -fasta " + pos_train_fa + " " + param_string + " -model " + model_file + print(check_cmd) + output = subprocess.getoutput(check_cmd) + assert output, "The following call of GraphProt.pl produced no output:\n%s" %(check_cmd) + if args.gp_output: + print(output) + profile_predictions_file = args.data_id + ".profile" + assert os.path.exists(profile_predictions_file), "Profile prediction output .profile file \"%s\" not found" %(profile_predictions_file) + + """ + Get 50 % score (median) for .predictions and .profile file. + For .profile, first extract for each site the maximum score, and then + from the list of maximum site scores get the median. + For whole site .predictions, get the median from the site scores list. + + """ + print("Getting .profile and .predictions median scores ... ") + + # Whole site scores median. + ws_pred_median = gplib.graphprot_predictions_get_median(ws_predictions_file) + # Profile top site scores median. + profile_median = gplib.graphprot_profile_get_top_scores_median(profile_predictions_file, + profile_type="profile") + ws_pred_string = "pos_train_ws_pred_median: %f" %(ws_pred_median) + profile_string = "pos_train_profile_median: %f" %(profile_median) + gplib.echo_add_to_file(ws_pred_string, params_file) + gplib.echo_add_to_file(profile_string, params_file) + # Average profile top site scores median for extlr 1 to 10. + for i in range(10): + i += 1 + avg_profile_median = gplib.graphprot_profile_get_top_scores_median(profile_predictions_file, + profile_type="avg_profile", + avg_profile_extlr=i) + + avg_profile_string = "pos_train_avg_profile_median_%i: %f" %(i, avg_profile_median) + gplib.echo_add_to_file(avg_profile_string, params_file) + + print("Script: I'm done.") + print("Author: Good. Now go back to your file system directory.") + print("Script: Ok.") + + +""" + +OLD CODE ... + + p.add_argument("--ap-extlr", + dest="ap_extlr", + type = int, + default = 5, + help = "Define average profile up- and downstream extension for averaging scores to produce the average profile. This is used to get the median average profile score, which will be stored in the .params file to later be used in a prediction setting as a second filter value to get more confident peak regions. NOTE that you have to use the same value in model training and prediction! (default: 5)") + + + p.add_argument("--disable-opt", + dest = "disable_opt", + default = False, + action = "store_true", + help = "Disable hyperparameter optimization (HPO) (default: optimize hyperparameters)") + p.add_argument("--R", + dest = "param_r", + type = int, + default = False, + help = "GraphProt model R parameter (default: determined by HPO)") + p.add_argument("--D", + dest = "param_d", + type = int, + default = False, + help = "GraphProt model D parameter (default: determined by HPO)") + p.add_argument("--epochs", + dest = "param_epochs", + type = int, + default = False, + help = "GraphProt model epochs parameter (default: determined by HPO)") + p.add_argument("--lambda", + dest = "param_lambda", + type = float, + default = False, + help = "GraphProt model lambda parameter (default: determined by HPO)") + p.add_argument("--bitsize", + dest = "param_bitsize", + type = int, + default = False, + help = "GraphProt model bitsize parameter (default: determined by HPO)") + p.add_argument("--abstraction", + dest = "param_abstraction", + type = int, + default = False, + help = "GraphProt model RNAshapes abstraction level parameter for training structure models (default: determined by HPO)") + +""" + + +
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/file1 Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,9 @@ +Open for business +Pain don't hurt +I love the smell of napalm in the morning +What are you gonna do? Bleed on me? +There's no crying in baseball +Nice night for a walk +I'll beat you like a bad stepchild +There's always barber college +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/file2 Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,9 @@ +Open for business +Pain don't hurt +I love the smell of napalm in the morning +What are you gonna do? Bleed on me? +There's no crying in baseball +Nice night for a walk +I'll beat you like a bad stepchild +There's always barber college +
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--- a/test-data/structure_test.params Fri May 25 12:17:44 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,6 +0,0 @@ -epochs: 50 -lambda: 0.0001 -R: 4 -D: 0 -bitsize: 14 -abstraction: 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.ensembl.fa Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,5 @@ +>ENST00000415118.1 cdna chromosome:GRCh38:14:22438547:22438554:1 gene:ENSG00000223997.1 gene_biotype:TR_D_gene transcript_biotype:TR_D_gene gene_symbol:TRDD1 description:T cell receptor delta diversity 1 [Source:HGNC Symbol;Acc:HGNC:12254] +GAAATAGT +>ENST00000448914.1 cdna chromosome:GRCh38:14:22449113:22449125:1 gene:ENSG00000228985.1 gene_biotype:TR_D_gene transcript_biotype:TR_D_gene gene_symbol:TRDD3 description:T cell receptor delta diversity 3 [Source:HGNC Symbol;Acc:HGNC:12256] +ACTGGGGGATACG +AAAA
--- a/test-data/test.fa Fri May 25 12:17:44 2018 -0400 +++ b/test-data/test.fa Wed Jan 22 10:14:41 2020 -0500 @@ -1,80 +1,5 @@ ->ENST00000620398 -ACTCTGGGAGGGCTAAGGAGCCATCATGATCCCTAAGCTGCTTTCCCTCCTCTGTTTCAG -ACTGTGCGTGGGCCAAGGAGACACAAGGGGAGATGGGTCACTGCCCAAGCCGTCCCTCAG -TGCCTGGCCCAGCTCGGTGGTCCCTGCCAACAGCAATGTGACGCTGCGATGTTGGACTCC -TGCCAGAGGTGTGAGCTTTGTTCTCAGGAAGGGAGGAATTATTCTGGAGTCCCCGAAGCC -CCTTGATTCTACAGAGGGCGCGGCCGAATTTCACCTCAATAATCTAAAAGTCAGAAATGC -TGGAGAGTACACCTGTGAATACTACAGAAAAGCATCCCCCCACATCCTTTCACAGCGCAG -TGACGTCCTTCTACTGTTGGTGACAGGACATTTATCTAAACCTTTCCTCCGAACCTACCA -AAGGGGTACAGTGACCGCAGGTGGAAGGGTGACTCTGCAGTGCCAGAAGCGAGACCAATT -GTTTGTGCCTATCATGTTCGCTCTACTGAAGGCAGGGACGCCATCACCCATCCAGCTGCA -GAGTCCAGCGGGGAAGGAGATAGACTTCTCTCTGGTGGACGTGACAGCCGGCGATGCTGG -GAACTACAGCTGCATGTACTACCAGACAAAGTCTCCCTTCTGGGCCTCAGAACCCAGTGA -TCAGCTTGAGATATTGGTGACAGTTCCCCCAGGTACCACATCGAGCAACTACTCCCTGGG -TAACTTCGTACGACTGGGTCTGGCTGCCGTAATTGTGGTTATCATGGGAGCTTTCCTGGT -GGAGGCCTGGTACAGCCGGAATGTGTCTCCAGGTGAATCAGAGGCCTTCAAACCAGAGTG -ACTCCATCTTGAACCGGGGCTGGGTAAACTGAGGCTGCAACCTGCTGGACTGCATTC ->ENST00000550775 -TCATGACTACACAGTTAAGGGTCGTCCATCTGCTTCCCCTTCTCCTAGCCTGCTTTGTGC -AAACAAGTCCCAAGCAGGAGAAGATGAAGATGGATTGCCACAAAGACGAGAAAGGCACCA -TCTATGACTATGAGGCCATCGCACTTAATAAGAATGAATATGTTTCCTTCAAGCAGTATG -TGGGCAAGCACATCCTCTTCGTCAACGTGGCCACCTACTGTGGTCTGACAGCGCAATATC -CTGAACTAAATGCACTCCAGGAGGAGCTGAAGCCCTATGGTCTAGTTGTGTTGGGCTTTC -CCTGCAACCAATTTGGAAAGCAAGAACCAGGAGATAACAAAGAGATTCTTCCTGGGCTCA -AGTATGTCCGTCCAGGGGGAGGATTTGTACCTAGTTTCCAGCTTTTTGAGAAAGGGGATG -TGAATGGTGAAAAAGAACAGAAAGTCTTCAGTTTCTTGAAGCACTCCTGTCCTCATCCCT -CTGAGATTTTGGGCACATTCAAATCTATATCCTGGGACCCTGTAAAGGTCCATGACATCC -GTTGGAACTTTGAAAAGTTCCTGGTGGGGCCTGATGGAATCCCTGTCATGCGCTGGTCCC -ACCGGGCTACGGTCAGCTCAGTCAAGACAGACATCCTGGCGTACTTGAAGCAATTCAAAA -CCAAATAGGAAGGTGGAGTTAAGGGCAGGAGCAACCCTACTTCTCACCTAATGACTTGCT -CTCCCCACCCCTCCAAAAAAAAGGAATACCCATCTTCTCACCACACTCTCTTCCTGCATG -GGCTCCACCTGAGTAAATCACCGCCACATACTGCCAGAATTCCCACTCTCCACAAACTAG -ATTTATATTTGGAAGGCTACTGCTCTTTTGCCTCTCAAGAGTATGTGGGTGAAGACTGAA -ACAAATGGAAACCTAAAATCCCCAGACCTCTGTTACAGGTTGAATCATTCATATCCACCA -GAGGGAAATCATCCTTCCACGACAATGGTTCAGTCGGCCATCACATCCTGAAGAACATTC -CTAGACATTCTGACTCTTCCATCTCTCTCTACCCTGGAGGTGTAGAAATAGCAATGGGGT -CACAGTCACACAATTTAGGTTCCACTTCATAACATTTTTTGTCTCCTAGGACAAACGTGT -ATCATCAGTTTCCAACTGTTTTGGCTCAGTTTTCATCCATGACACCTCCCCCTACCAGCC -ATTCTCCTGTGGGAGCAAGAACATTGCTTCAAAAGAAGAGAGGGCATCTCCATGCTTGTG -GGACCCAAAACCTATCTCTGGCCCTACAAAAGTTTTCCTAATTGTCTGATCTTTAGTGCA -TTCAGGTTATGGCACCTGGAGAGGAATGCCCTTTATCTTTTGAAGGATGGGATTTCCCAT -CTCAACCCTGGATTCCTCACCTTCAGAACGAGCCCTGCCACTGTCTCCAATAAAATGTTT -TCTGCAGCATCG ->ENST00000622300 -TAGTTTCCTGTTTCCGGCTTCGCTTCGGCCCACCCCCACGTCCACCCCGAATCCCTGCTT -AAAGGCCTTGCTTTCTTGTCTAACGCCGCAACCAGTCCTCTGAGTTGCCAACGTCTTTCT -TCTTGTCTCGACGCCCCGTCGTCCGGCCACAGCGATTCTCTGCTTAGCAGGATCGGTCCA -CAGCGGGACGTGAGTCCCTTTCCTCCTCGCGGCTTACCGCCTCTCTCCGCCTAGTGCCAG -GTGCTAATAAAGTTGTTGTTTCAAATGCGGCCAGGAACATCGCGAGCGGGGACCAATCAG -AGAGTAGCTTTGCCTCTATAACGGCGCGAGAGTGAGACGTCATCGGTGAGCGACTAACGC -TAGAAACAGTGGTGCGCGGAGAGGAGAGGCCTCGGGATGTCTCTGGCAGATGAGCTCTTA -GCTGATCTCGAAGAGGCAGCAGAAGAGGAGGAAGGAGGAAGCTATGGGGAGGAAGAAGAG -GAGCCAGCGATCGAGGATGTGCAGGAGGAGACACAGCTGGATCTTTCCGGGGATTCAGTC -AAGACCATCGCCAAGCTATGGGATAGTAAGATGTTTGCTGAGATTATGATGAAGATTGAG -GAGTATATCAGCAAGCAAGCCAAAGCTTCAGAAGTGATGGGACCAGTGGAGGCCGCGCCT -GAATACCGCGTCATCGTGGATGCCAACAACCTGACCGTGGAGATCGAAAACGAGCTGAAC -ATCATCCATAAGTTCATCCGGGATAAGTACTCAAAGAGATTCCCTGAACTGGAGTCCTTG -GTCCCCAATGCACTGGATTACATCCGCACGGTCAAGGAGCTGGGCAACAGCCTGGACAAG -TGCAAGAACAATGAGAACCTGCAGCAGATCCTCACCAATGCCACCATCATGGTCGTCAGC -GTCACCGCCTCCACCACCCAGGGGCAGCAGCTGTCGGAGGAGGAGCTGGAGCGGCTGGAG -GAGGCCTGCGACATGGCGCTGGAGCTGAACGCCTCCAAGCACCGCATCTACGAGTATGTG -GAGTCCCGGATGTCCTTCATCGCACCCAACCTGTCCATCATTATCGGGGCATCCACGGCC -GCCAAGATCATGGGTGTGGCCGGCGGCCTGACCAACCTCTCCAAGATGCCCGCCTGCAAC -ATCATGCTGCTCGGGGCCCAGCGCAAGACGCTGTCGGGCTTCTCGTCTACCTCAGTGCTG -CCCCACACCGGCTACATCTACCACAGTGACATCGTGCAGTCCCTGCCACCGGATCTGCGG -CGGAAAGCGGCCCGGCTGGTGGCCGCCAAGTGCACACTGGCAGCCCGTGTGGACAGTTTC -CACGAGAGCACAGAAGGGAAGGTGGGCTACGAACTGAAGGATGAGATCGAGCGCAAATTC -GACAAGTGGCAGGAGCCGCCGCCTGTGAAGCAGGTGAAGCCGCTGCCTGCGCCCCTGGAT -GGACAGCGGAAGAAGCGAGGCGGCCGCAGGTACCGCAAGATGAAGGAGCGGCTGGGGCTG -ACGGAGATCCGGAAGCAGGCCAACCGTATGAGCTTCGGAGAGATCGAGGAGGACGCCTAC -CAGGAGGACCTGGGATTCAGCCTGGGCCACCTGGGCAAGTCGGGCAGTGGGCGTGTGCGG -CAGACACAGGTAAACGAGGCCACCAAGGCCAGGATCTCCAAGACGCTGCAGCGGACCCTG -CAGAAGCAGAGCGTCGTATATGGCGGGAAGTCCACCATCCGCGACCGCTCCTCGGGCACG -GCCTCCAGCGTGGCCTTCACCCCACTCCAGGGCCTGGAGATTGTGAACCCACAGGCGGCA -GAGAAGAAGGTGGCTGAGGCCAACCAGAAGTATTTCTCCAGCATGGCTGAGTTCCTCAAG -GTCAAGGGCGAGAAGAGTGGCCTTATGTCCACCTGAATGACTGCGTGTGTCCAAGGTGGC -TTCCCACTGAAGGGACACAGAGGTCCAGTCCTTCTGAAGGGCTAGGATCGGGTTCTGGCA -GGGAGAACCTGCCCTGCCACTGGCCCCATTGCTGGGACTGCCCAGGGAGGAGGCCTTGGA -AGAGTCCGGCCTGGCCTCCCCCAGGACCGAGATCACCGCCCAGTATGGGCTAGAGCAGGT -CTTCATCATGCCTTGTCTTTTTTAACTGAGAAAGGAGATTTTTTGAAAAGAGTACAATTA -AAAGGACATTGTCAAGATCTGTC +>seq1 +acgtACGTacgt +>seq2 +tgcaTGCAtgca +ACGTacgt
--- a/test-data/test.model Fri May 25 12:17:44 2018 -0400 +++ b/test-data/test.model Wed Jan 22 10:14:41 2020 -0500 @@ -1,3 +1,3 @@ -bias 0.0990594 -wscale 0.000419047 -w 3:-2.6323795e+02 7:-1.5498299e+02 39:3.2710247e+01 90:-9.6892609e+01 92:-6.2059918e+02 102:2.7361217e+01 108:-1.8683072e+02 111:9.2224388e+01 121:4.4261597e+01 127:-2.9686353e+02 148:-2.4798018e+02 155:1.0929895e+02 212:-3.0733829e+02 217:-3.6330551e+02 219:4.3392648e+02 220:-4.3969490e+01 223:-1.2370902e+03 235:-2.5857092e+02 286:-4.4877792e+01 306:-3.2496075e+02 308:-2.0045505e+02 375:-2.3125467e+02 396:-6.7614136e+02 400:1.1828072e+02 408:4.3950644e+00 414:2.0196147e+03 421:-3.3002304e+01 431:-4.0940579e+02 432:-5.0269598e+02 434:-1.4379294e+02 469:-4.2782242e+02 486:1.9116473e+02 492:-1.6351070e+02 496:-3.4013925e+02 502:1.6938168e+02 524:9.0154556e+01 541:-3.2447818e+02 542:-3.8114508e+02 546:1.8973650e+02 605:2.8628244e+02 609:-2.4498466e+02 615:4.9888785e+02 617:-7.0967567e+01 626:-7.4189880e+01 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--- a/test-data/test.params Fri May 25 12:17:44 2018 -0400 +++ b/test-data/test.params Wed Jan 22 10:14:41 2020 -0500 @@ -1,19 +1,18 @@ epochs: 20 -lambda: 0.001 +lambda: 0.01 R: 1 -D: 4 +D: 3 bitsize: 14 model_type: sequence -#ADDITIONAL MODEL PARAMETERS -ap_extlr: 5 -gev_my: -2.5408 -gev_sigma: 1.6444 -gev_xi: -0.1383 -p50_score: 6.51534 -p50_p_val: 0.0009059744 -# ADDITIONAL MODEL INFO -organism: hsa -rbp_ens_gene_id: ENSG00000011304 -rbp_gene_name: PTBP1 -clip_method: eCLIP -pubmed_id: 27018577 +pos_train_ws_pred_median: 0.760321 +pos_train_profile_median: 5.039610 +pos_train_avg_profile_median_1: 4.236340 +pos_train_avg_profile_median_2: 3.868431 +pos_train_avg_profile_median_3: 3.331277 +pos_train_avg_profile_median_4: 2.998667 +pos_train_avg_profile_median_5: 2.829782 +pos_train_avg_profile_median_6: 2.626623 +pos_train_avg_profile_median_7: 2.447083 +pos_train_avg_profile_median_8: 2.349919 +pos_train_avg_profile_median_9: 2.239829 +pos_train_avg_profile_median_10: 2.161676
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,2 @@ +s1 5 8 s1,6 6.500000 + +s2 3 6 s2,4 4.000000 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.peaks_genomic.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,2 @@ +chr1 1000 2000 s1 0 + +chr2 1000 2000 s2 0 -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.predictions Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,3 @@ +SERBP1_K562_rep01_2175 1 0.0193945 +SERBP1_K562_rep01_544 1 0.571673 +SERBP1_K562_rep01_316 1 0.978629
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,9 @@ +0 0 -2.1 +0 1 1.9 +0 2 1.1 +1 0 -2.1 +1 1 3.2 +1 2 1.1 +2 0 -2.1 +2 1 4.1 +2 2 1.1
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test.sequence_motif Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,437 @@ +ACACCCCAGCAG +CGCCGCCGCCGC +GGAGGCUGCCCG +GCCCCGGAUUGC +CGCCAACCGCCG +GCCGAGCUGCAC +GCCGAGCCAGAG +GCGCAGGGGCCC +GAGCCACCUGGA +CCUCGACGGGAG +CGCAGGGACCCC +GCCCGGGCCGCC +CCGCCGCGCGCC +CCUCCGCUCCCG +ACCAGCGCCAGG +CGCCCGUGCCAG +GCCGCCGCCGCC +GCCGCCCUCCGC +CGCCUGCCCGCC +CCAGCAGCAGCC +CGAGCGCUGCCG +CCGCCGCUGCGC +CAGCGGCCCCGC +CAGGGCUGCUGG +GAACCGUGCUGC +GCGGCCGCCGCG +CGCGGCGCUCGC +CUGGCCAGGGCC +AGCCAGGCUGGA +CGGGGCCGGGGC +CGGCCAGCGGGC +GGACGGCAGGCC +CGGCCGCCAGAA +GCGCCUCCCGCG +CCUGCCGUCGCG +GCUGCCACAGUU +GGCGGAUGCCCC +CCAGCCAUCCCC +GGGCCCCCACCG +CUGGACGCGUCC +CCGGCGUUCAAG +GAGCAGGAGCGU +CGAGAGCGGCCC +CCGAAACCGAAC +CCACUCCCCGCC +CGGCGGCGGCGC +GAGGGGAAGCUU +CGCAUGCGGAGG +CGCGGAGGAGCC +CCUGGCGCGAGA +CCGAGCAGCCGC +GCCCUGGAGGGC +CGGCGCCCCGCC +CCGCACAGCAGC +GCGGCGACGACC +GCCCCUUGCCGA +GGAUCCACGGGA +GGCAGGGCCGGG +GGAGCCGCCACC +CGAGCCCUGCCC +GAGGCCGGACCC +CCGGAGCUGCCG 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+CGGCGCCAAGUU +ACCAGAUGGUGA +CGGAGGGCCUGC +ACCUGCUGAUGA +GCGCCGCGCGCC +GGAGGAGCAGAU +ACCCCUGCAGCC +GCCGGCUUACCA +CAACGCCCUGUG +GCCGACGCCGCG +GCCGCCUGGACA +CAAGGACGAGCC +GCUGGAGCCCCA +CGCGGCGGCGGC +AUCGCCGAAGCU +CCCCGUUCACAA +ACCUCCCAGGGC +GCCGGCCACCUG +ACCGGGGAGGGC +CUGCCGCCCCCG +CCGUGGCGGCUU +CCGGCCCGGCGC +CGGCGGCGGCGC +CAAGAAGAACCC +GGAGACGGCGGC +CCACCAAAGGAG +GCUCCGAGAAGC +GAGACCCGACGC +GCAGCCACCGCC +GCAGCCCCCCGU +ACCAGAGCUGCC +CCGCUGCGCGGC +GCCGCCGCCGCC +AGGAGGCGACCG +CGGACCGCGCGG +GCCGGGGCUUCU +CCCCGGGGAGGA +GCCACCCCCGGG +GCCCCAGCAGCA +CAGCCCCCAAGA +CCGCCGCAACCA +CUGCCCCUGCCC +GCUUGCCCAGCA +GCCCGGCGCCGC +CGGCCCCAGCCG +GCUCCUGAAGCC +CCGCUGCGGCCG +GCAUCAAGGAGC +GCGAGCAGAAGG +CCAGAACCAGGG +ACCAACAACCGC +GCCCCCCGACCA +CAGCCGCCCCGC +UGCUGGCCGGGG +AGCACCUCCGCC +CAACUGGCAGCU +CGCCACCGCCGC +CCCGGGCGGAGC +CCAACCGGCCGC +GACCGGCGCAGC +GGCCCUGGCCAC +GACCCCUGACGG +CUGCUGGCAGGC +CUGCCGCCCAAC +GCGGCGGCGGCG +CGCCCAGCACGC +GCCCAGGCCCCG +GCGCAGCCCGGC +AGGCGUCGGGCG +CCACCGCCACCG +CUGGCAAGCAGC +GGCGGCGGCGGC +GCCCCCUCGGCC +GCCCCAGCCCCC +GCCAUGCACGCC +GGACGAGCGCGA +CCGUCGUCGCCG +GACCACUCAGCC +CACGCCAGGCCA +CGGGACGCGGGC +GGCAGGAGCGCG +CCCAGCAAGUGC +CGUGGCGUGGCC +GCCGGCCCCCGG +GAGCAGCGGAAG +GCCCGCCUGUCC +GGCCCGACGGGA +CCCGGACUCUCC +GCCCCCAUCCCC +AAGAACUGGGAG +CGCCGAGCUGUC +GAGCAAGCCAUU +GGAAGCUGGGCC +CUGGAGCCCAUG +CGCCCAAGAAGC +GGAGCUGGACCC +CCGCGCCGGCGC +GUCCCAGCAGAC +GGCGAGCCUGGC +CAGCUGCGGGCG +GCAGCAUGCUGC +CCAGCCCGCCCC +CGCCGCCGCCGC +CCGCCGACCCCC +GCCCCAGCCCAG +GCGGCGGAGGCC +CGGGCCCGGGCG +CGCCGCCUCCGC +GCGCGGCGGCCG +CUCCCCCAACUA +ACGAGCGCUGCA +CGGCGCCGCGCG +GGCCGCGCAGCA +GGCCCCGCGGGC +CGCCCACCACGG +GGGCGGCCAGGC +CCUGGAAGCCCC +CCGCCAUCAGAA +GACAGCGCCACA +CGAGCGCGCCGC +CCCAGGGCCCCA +CCGCAGGGGCCC +GCGGGCGGCGGC +CCCGUGCCAGAG +CCUGCCGCCGCG +ACAGACAAGCCC +GCAGCACAGGCC +CCAGCUCUGCCC +GCCAAGGAGGCG +GGCAAGCCCACC +GCGGCGGGCCAG +CCUGGCCCCCAC +GCGCCCGGCGAG +CCACCCUAUUCC +CGCGCCCCGCGU +CGCCCCCGCCCG +UGACCAACCGAC +CCCGGCGGCCGC +GGCCACGCGGGC +CCGCGCCGCCGC +CAGCGCCGCACC +GCCGCCAGAACA +CGACCACCACCA +GGGCACUGGACC +CCCCAGCCCCGC +CCACCAAGGCAC +CCGAGGCGGCGC +CCGAGCGAUGGG +GCCCCAGGACAC +GCGGCGGCCCCG +CCGCCGCCGCCG +GAAGGGCCGGCG +GCUGCCCCUGGC +CGCCUCGGAGGC +CCCAUCCCCACC +GAAGACCGGCGA +GCAGACCCCUGC +GCGGAAGGUGGA +GGUGCGGGAGGC +CGAGCAGUGCUA +GACGCCAGCGGC +GGGCGCCGCCGC
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test1.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,7 @@ +chr1 1000 2500 CLIP1 1 + +chr1 3000 4000 CLIP2 0 + +chr1 5000 6000 CLIP3 2 + +chr1 7000 8000 CLIP4 3 + +chr1 9000 10000 CLIP5 1 + +chr1 11000 12000 CLIP6 0 + +chr1 13000 13500 CLIP7 3 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test2.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,4 @@ +chr1 1000 2000 CLIP1 0 + +chr1 3000 4000 CLIP2 0 + +chr1 3000 4000 CLIP2 0 + +chr1 7000 8000 CLIP3 0 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test2.profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,19 @@ +0 0 2 +0 1 3 +0 2 5 +0 3 8 +0 4 4 +0 5 3 +0 6 7 +0 7 1 +1 0 3 +2 0 2 +2 1 3 +2 2 5 +2 3 8 +2 4 4 +2 5 3 +2 6 7 +2 7 1 +3 0 2 +3 1 4
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test2_1.avg_profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,19 @@ +0 1 3.333333 +0 2 4.500000 +0 3 4.400000 +0 4 4.600000 +0 5 5.400000 +0 6 4.600000 +0 7 3.750000 +0 8 3.666667 +1 1 3.000000 +2 1 3.333333 +2 2 4.500000 +2 3 4.400000 +2 4 4.600000 +2 5 5.400000 +2 6 4.600000 +2 7 3.750000 +2 8 3.666667 +3 1 3.000000 +3 2 3.000000
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test2_2.avg_profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,19 @@ +0 1 3.333333 +0 2 4.500000 +0 3 4.400000 +0 4 4.600000 +0 5 5.400000 +0 6 4.600000 +0 7 3.750000 +0 8 3.666667 +1 1 3.000000 +2 1 3.333333 +2 2 4.500000 +2 3 4.400000 +2 4 4.600000 +2 5 5.400000 +2 6 4.600000 +2 7 3.750000 +2 8 3.666667 +3 1 3.000000 +3 2 3.000000
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test2_3.avg_profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,19 @@ +0 0 2 +0 1 3 +0 2 5 +0 3 8 +0 4 4 +0 5 3 +0 6 7 +0 7 1 +1 0 3 +2 0 2 +2 1 3 +2 2 5 +2 3 8 +2 4 4 +2 5 3 +2 6 7 +2 7 1 +3 0 2 +3 1 4
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test3.fa Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,6 @@ +>SERBP1_K562_rep01_544 +CAGGTCCCTCCTCCGGCATGTGTCAGCGCAACCCCCAGGTCTGCGGCCCAG +>SERBP1_K562_rep02_709 +CTCCAAGGGCGGGCTTGTGCTCTGGTGCTTC +>SERBP1_K562_rep01_316 +GGCTCCGCTGTACAAGAACGTGGATGTGCGAGGTATCCAGG
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test3_added_ids_exp.avg_profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,19 @@ +s1 1 3.333333 +s1 2 4.500000 +s1 3 4.400000 +s1 4 4.600000 +s1 5 5.400000 +s1 6 4.600000 +s1 7 3.750000 +s1 8 3.666667 +s2 1 3.000000 +s3 1 3.333333 +s3 2 4.500000 +s3 3 4.400000 +s3 4 4.600000 +s3 5 5.400000 +s3 6 4.600000 +s3 7 3.750000 +s3 8 3.666667 +s4 1 3.000000 +s4 2 3.000000
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test3_added_ids_out.avg_profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,19 @@ +s1 1 3.333333 +s1 2 4.500000 +s1 3 4.400000 +s1 4 4.600000 +s1 5 5.400000 +s1 6 4.600000 +s1 7 3.750000 +s1 8 3.666667 +s2 1 3.000000 +s3 1 3.333333 +s3 2 4.500000 +s3 3 4.400000 +s3 4 4.600000 +s3 5 5.400000 +s3 6 4.600000 +s3 7 3.750000 +s3 8 3.666667 +s4 1 3.000000 +s4 2 3.000000
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test4.avg_profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,18 @@ +s1 1 -1 +s1 2 0 +s1 3 2 +s1 4 4.5 +s1 5 1 +s1 6 -1 +s1 7 5 +s1 8 6.5 +s2 1 -1 +s3 1 -1 +s3 2 0 +s3 3 2 +s3 4 4.5 +s3 5 1 +s3 6 -1 +s3 7 5 +s3 8 6.5 +s4 1 4
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test4.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,2 @@ +chr1 10 20 CLIP1 0 + +chr1 30 40 CLIP2 0 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test4_out.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,3 @@ +s1 1 8 s1,8 6.500000 + +s3 1 8 s3,8 6.500000 + +s4 0 1 s4,1 4.000000 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test4_out_exp.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,5 @@ +s1 1 5 s1,4 4.500000 + +s1 6 8 s1,8 6.500000 + +s3 1 5 s3,4 4.500000 + +s3 6 8 s3,8 6.500000 + +s4 0 1 s4,1 4.000000 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test4_out_exp2.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,3 @@ +s1 1 8 s1,8 6.500000 + +s3 1 8 s3,8 6.500000 + +s4 0 1 s4,1 4.000000 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_exp.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,2 @@ +chr1 1005 1008 s1,1006 6.500000 + +chr2 1994 1997 s2,1997 4.000000 -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_negatives.parop.fa Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,50 @@ +>random_negative_9901 +GCTAGCTATAATTTGCCCTCTGAGGATTGTAATACCGAGAAACAGATGGTTTCTCACAGTA +>random_negative_19543 +ACCTCAGCCTCCCAAAGTGTTAGGATTTACAGGCATGAGCCACTATGCCTGGTCATTTTAT +>random_negative_3739 +TGCAGGCGTACATCTTCCTTCTGCAGTGTCCTTCCAGTGCCTTTTACAGAGAAAGGTTAAT +>random_negative_21923 +TGAGGCACCCGGCTTCCGGTGCCTCTGGCAGCCCAGAGAAGTGACTCTGTCTGTCTTAAGG +>random_negative_134 +CAAAGTGCTGGGATTACAGGCGTGAGCCACTGCGCCTGGCCTGTTTTTGGTCTTTTCTGTT +>random_negative_5629 +TCTGTGACCCAGGCTGGAGTGCAGCAGCACAATCTTGGCTCACTGCAACCTCCGCCTCCCA +>random_negative_18032 +GTGCAGCTTCCAGACAAGTCTCTTAGACCTCATCCTCAGTCTCACCCTGACTGACAAGTTT +>random_negative_17947 +CGTCATTTACATTAGGTATATCTCCTAATGCTATCCCTCCCCCAGCGCCCCACCCCTCGAC +>random_negative_4666 +GAGGTGCGCCTGTGTGGAGATCTGAGGGTGACGTAAGTAGAGGCACTGGCGTGAGGGCCCC +>random_negative_3271 +TCTTTGTAGGGAGCAGGGAGAGTGATCTCAGCTGGTCTCTGGGATTGGGAAAAAGTGTGAT +>random_negative_10185 +CCTGCATGCCTGCCTTCTGCCCCTGCCGAGGCTGGGTCCTAGGGGAAGCACTTACTTCCCT +>random_negative_15116 +CTACTGATGTGGAAAGTGGCATCTATGGGAAGGTTATCTCCTAACTGGCAGAGCAAGGTCA +>random_negative_19846 +GTCTGAGGGGAGAGGTGCATTTCATAGACCCCCATAGTGCTCCTTATGTCGGGAGCTTACA +>random_negative_14690 +TTCCTCGCCTGGCGTGTCCGCTCCCTCCCTCCCTCTCTGCTCTGGTCGCGCCCGCCCACTT +>random_negative_4674 +TTGGCCCCTTGGTTTTTCCCCAGGTAGCTGTGGTAGTGCAGGGGCAGCTCCCTGCCCCTTC +>random_negative_18030 +CCTGGTAGTGCCAGCTGGTGTCTTGCCAGCCAGAGCACAGCCCCGCTTGGTCAGGAATGCA +>random_negative_3289 +TTTTTCAAAGTCAAAAAAAGAAATGTGACAAAGTGCTCTGGAAATTTACTGGAATTCTTGA +>random_negative_6275 +TAACCTTTCTGTGCTATTTCCCTATCTGTAAAAAGAAGAAGAGATGGTACCGATCTCCCAG +>random_negative_11324 +ACTCCATTAACTCCACCCACCTCCTGCACCCCTCCCCACACACACAAAATGAACCACGTTC +>random_negative_8258 +AACCCGGGAGGCAGAGGTTGCAGTGAGCCAAGGTCACACCACTGCACTCCAGCCTGGCCAA +>random_negative_16662 +TCAGGCTACATTAGAACACTTGCTGTTTCCCCAATATATCATGTGCTCTTGGGCCTCTGTG +>random_negative_6703 +TCTTGGGAAACCAAGAGCAAGGAAATGCCAGCAGATCTCATGAAAAAACTGCAACCAGGGT +>random_negative_10199 +CACCTGGGGCTGCGACTGGGACAGTGTCCCGTGTGCGGTCCCTCCTGCGGGTGACACAGGA +>random_negative_13581 +ATGTTATGTGTAAAGGCGGCGTATCCTTTGGGAGGCTGAGGTGGGAGGATCGCTTGAAGTT +>random_negative_17232 +GATGGGTGGGTAGATAGCTGGTGGATAAGTGGATGGATGGGAGGATAACCAGGTGGATGTA
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_negatives.train.fa Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,1000 @@ +>random_negative_21583 +CCCAGGAATTTCATTGTGCATATCCCTCAATTCAGCACATACTAGAAGTGGGAATACAGCC +>random_negative_22306 +CGTGTGGAAGAACAAAGAGCTAACTTTTCAAAGCAGGTTTCTCCAATGGAGGGTGGGGTTG +>random_negative_7272 +ACAGAAGGGGTCCATGTAGAATTTCGTTTCTTCCTGGAAGTCCCAAGGAAACCTGCAAGTA +>random_negative_16884 +GTACACCGTTCTTCCTGTTCTAATAAATAGCTTTCAGAGTCATACCTCAGCATCTTGTCTT +>random_negative_20197 +TGCTGAGCGGCTTGGCCTGCAGCGAGGCCCCCTCCCACCTGCCATGCTCTCTTGCTGGCCG +>random_negative_10981 +ATATAAAAATGAAATTAAGAAAACAATTCCTGGCTGGGTGTGGTGGTGAGTGGGTCACCTG +>random_negative_15764 +TAGGGGCTGTGCTCTTGGATCTGGACCAGCAGACCCTGCCCGGAGTGGCCCACCAGGTGGT +>random_negative_15445 +AGGGAAGGCAGTTTGATGCCTGGAGAGGGACCCGTGGCTTCCAGCTGCCAGGCCAGCCCCA +>random_negative_11194 +CTCCCATGTGACCCCTGCATTCCCTCTCCTGCTGTGCCTTTGGAGGGCCCCCATCTCTCAT +>random_negative_20933 +TCCCCCAAAATTGAAATGATGCTTCTTTCTACTCTCAGCCACTACACCATCCCCCCCGAAT +>random_negative_6890 +AAAGAAAATGAGAGGTGGAATGTTATTTCTAAATCACAGTTGAAGAACATTAAAAAGATGT +>random_negative_7130 +CTGCAACCTCCGCCTCCCCGGTTCATGCGCCTCGGCCTCCCAAAATGCTGGGATTGCGGAT +>random_negative_20989 +GCTGTAGTCCAAGGGGAAGGGTCCCTCTCGCTTCACCCTGTCCTGGGTCTCCCCAGGTGAG +>random_negative_9619 +AGGTGTGTGCCACCACATTTGGCTAATTTTTATATTTTTAGTAGAGATGGGGTTTTACCAT +>random_negative_20105 +CAGGCATGCGCCACCATGCCCGGCTAATTTTGTATTTTTAGTAGAGACGGGGTTTCTCCAT +>random_negative_7706 +ACAGGCATGTGCCACCACACCTGGCTAATTTTTTTGTATTTTTAGTATAGACAGGGTTTCA +>random_negative_3555 +GATAACATAATCACCAATTTGAGATTCTGTGTTCCTTTTGCTTTTTGTATTCTTTATGGAA +>random_negative_6700 +GCCCCCCAGAAAGCATGCAATGTCCCTTAAAGTACACTGTCCCTTCTACTCACAAAGCAAG +>random_negative_6780 +CTCGACCCGTCCTTCACTCACGCCATGCAGCTGCTGACGGCAGGTAAGGGGGCCTCCCGTG +>random_negative_22232 +GCCGGGCCGCGGGAGGGCGGAGGAGTTGGCGCGCCGAGCGCTCGGCCCGGGGAGCGGTTTT +>random_negative_14067 +TTGGGGAATTGTGGTCCCTAAATAGGAGGGTTTGGGGGCCCCGGGCCCCCGCGAAGGATCC +>random_negative_9526 +GGTTTAAGCAGTGTGGCATTGGCTTATTTTGGCTAACCCTAGACTTCCTAGATTTTACAAG +>random_negative_18033 +GTCCTCACTGCTACTCTCCCACCAGCACTATGACTGTTTAGAAATGCCATGGCAACATCAG +>random_negative_19284 +TGGAAAAGGGGACACGAAGGCCAGTGGCTTCCTGTGTCGCTGGGCAGCAGGCCGCCTCCAG +>random_negative_7687 +ATGACTTTTTTCATAGCAAAGATGTAGATCAGATATGAAATTAGGATAAAACAAGTTTTTT +>random_negative_6511 +AAGGGGCCACCAGGCTGGGCTCTTCTGGGGATGATGTGGAAGCTTGCTGGCTGGGCCGGGG +>random_negative_3242 +ACAGTACAGCAAATTATGAAGTTCCTTTCAAGTCAGAAGTTTGTTCCTGGGCCCTTAAGAC +>random_negative_19073 +TTGGAATATATTTTGATCTGTCATCTAAGTATGAATTTGGCTGTAACTCTGCTGTTAAATG +>random_negative_16680 +TTACATAGTGGTAAAGGGATCAACACAACAAGAAGAGCTAACTGTCCTAAATATATATGCA +>random_negative_22939 +GGGTATGGGGTTTCTTTTTGCAGTGACAGAATGTTCTAAAATTAGGTAGGGGTGCTGGTTA +>random_negative_21512 +TGGCACAAATGGAAGGGAGGGAGCTAGAAGTCCTCGGTGGCATGGAAGGGCCCGGAGGCTC +>random_negative_3569 +CCACCTAGGCTGGAGTGCAGTGGCACAGTCATGGCTCACTGCAGCCTCAACTTCCCAGGCT +>random_negative_5606 +ATGTAGCACAGTTTCTTTGTCCATTCATTTGTGGATGGATACTTAGGTCAATTCCGTATCT +>random_negative_4927 +CTCATCAGTTTGTATTCAAACGCTTCCAGCCATGGAAAGTCTCAGGGCAGGGCCAGCAGGG +>random_negative_16654 +ACATTTGGACTGGTTTCATGAAACATTAATATCTCATTAATTGTACAGTTATTATTTTAAC +>random_negative_11557 +CAGGAAGCTCCAGGACTCCAAGGTCTCCAGGCTGAATGTCCCTGCATCCCAAGGATAGGCC +>random_negative_1151 +CTCACTGCAAGCTCTGCCTCCTGGGTTCACGCCATTCTCCTGCCTCAGCCTCCCAAGTAGC +>random_negative_729 +CATGGGCGTCCCTGCCTCCCAGAGCGTTAGCGATTCCTTTTCCCCCAATACGTGCTCTTCC +>random_negative_395 +TGACAAGTTAGCCATTTAGAGAGCTGAAACATTCAAGTAGTTTTTAAACAAAAGCAATCAT +>random_negative_7892 +ATACAAAATTAGCCGGGCATGGTGGCATATGCCTGTAATCCCAGCTATTTGGGAGACTGAG +>random_negative_3722 +GAATTTATATAATTAACTTTCACAACAGCCGTTTCTGTTAGTCAGCAGTAAACTGAAGGGA +>random_negative_12331 +TCAAGAGAGCAGAACTTGGTAGGCTCCTGGCCTTGGGTAGCTAAGGTTTGGAGGAGGTGGA +>random_negative_18482 +CAGTAATGGTGGATGCCCCTTCCCTAGCCTCGCTGCCGCCTTGCAGTTTGATCTCAGACTT +>random_negative_14968 +CTCAAAGTCATTACTGACCACACTTCAGATTTAGCCATGTATAATATTCACTGATATGTAG +>random_negative_21401 +CTGCAAGCTCCGCCTCTCGGGTTCACGCCATTCTCCTGCCTCAGCCTCCCAAGTAGCTCGG +>random_negative_3422 +TTTGAGCCCGAAGGACTCACAGAGGTCATCTACTCCAATTATTTTCTTTTCCCTCTGCAGA +>random_negative_15125 +TCAAGCTGCAGTCGTTTGGGGTGTCTTCCCTGGTTTCCCTCTCAACTATACAGTAATTGCT +>random_negative_11309 +CAAGATTTTTGGCATGTTCAAATATTCTGTGTCTTTCTATGAAATGCTCATGCAGGGCTGT +>random_negative_5388 +CGATGAACCCGCCAGTGACTCTGCAGCTGGGGTCATTCCAAGTTCACGCAGTGGACTTTTG +>random_negative_11825 +ATACAGAATTGACTACACAAGCTTTCTGCTCAAAGTGTGGGCTATGGAGACATCTAGGAAA +>random_negative_11762 +TCTCCCAGTGGGGTACACAGCTGGGACCACCTCAGTGCACAGGAGAGAAGTGTGTCCCGCG +>random_negative_1605 +CCCGAGTAGCTGGGACTACAGGCACGTGCCACCAATGCCCAGCTAATTTTGTATTTTTAAT +>random_negative_1945 +TGTATCGCTTGAGCTCAGGAGTTTGAGACCAACCTTGGCAACATGGCAAAATTCCATCACT +>random_negative_3458 +CCACCCACAGTAAAAAGACAAATTCTAAAAATTAAAAAAAAGCGCATAATTACCAAAAAAA +>random_negative_17640 +CGGGGATGGGAGGCTGCAGCTTCGGGGCTGTGTCGAGGGAGCAGGCCCCGCTCTCCTTCCT +>random_negative_19814 +TATGTGAGCGGGAAGGTGGTGGGGCCAGGCTGCCTGGCAGGAGAAATGCCCTCATTGACTT +>random_negative_2743 +CACCTAACTGCCTGTGCCGATCTCTCTCATTCTGACACTTGGCTCCTGAGGGATCTTTACT +>random_negative_4785 +GAAAGAAGAAAGCATTGTATCTCGAGGGCAAGCAAAGGGTCAGGACTTGTTCAAGCTCAAA +>random_negative_17872 +GGGAGGATTGCTTGAGCCCAGGAGTTCACAGCTGTGGTGAGCCGTGATCGCGCCACTACAC +>random_negative_4344 +GGAGGGGAATGGGCAGCTTGTATTTGCCCATTCTCTTAGTTAAGAGGCACCCAATCCCTGT +>random_negative_22239 +AGCAAGAAGCTCTCAGAGCCTGAGCCCTGGGTCTGAATCTTAGCTCTGCCAGGCCTGGCTG +>random_negative_1871 +AGGTGTGGTGGTGACAAGCTGCAGGGACAGGTATCAAAAGTGAACATAGCAGAGAATGGGG +>random_negative_1392 +CTGGAAACAACACAAATGTGCATCAACAGTTGAATGAATTAATAAAGTTTGGTAAATAGAG +>random_negative_7078 +ACTGAGGTCAGAGTTGCACAGCTTTGGACAGATAGCCTGGACACAGGAAACCATGTTCTCT +>random_negative_971 +TTCCTAAAGGTATTTCGCTGTGAATTCAACCAATTCTCTACAGAGCTCAACAGGATGGTCT +>random_negative_16670 +CACTGTATGGTATATATGGTATACATATATATGTATATATGGTGAACTACCCAAAAATGAA +>random_negative_647 +CTACCCTGTCTCCTGGTCCCGTCAGCGTGACTTCTGCAGGACTCTAGCTTTAGCTTTGTTC +>random_negative_5372 +TCCTCCAGCCTCCTGAATGGCTGAGACTACAGGCGCACGCCACCATGCCCAGTTAATTTTT +>random_negative_5319 +TGGAATTGGGTTGTTCATCCTTTTCTTATTGATTGTTAGGAGCTGTTTGTATATTCTGAAT +>random_negative_8821 +GGCAGAGCCGGGAGGTGCTATGCAGAGAAGGAAGTGCAGTGTGAGCCTTCTGACCAATGCA +>random_negative_21189 +TGCTAGTATTTGAAAACACAATGATTTCATATAAAAACCTGGATTAATAGTTTATTTTAAA +>random_negative_2306 +GGGAGCCTAACTCAGCTTAGGTGGTCAGAGAGCACTTCGTGGAGGAGGGGACCCCCATCCG +>random_negative_10139 +TTTTAATAGGATCATTCTGGCTGCTCTGTTGATGGGAGGAAGATGGAATTAAGGAGATCAG +>random_negative_19094 +ACTGGAGCTTGCTTTTCCTCCAGTGCTGTCACCCTCGTATTCATTCATTCCTACTTCTTGG +>random_negative_57 +GGGTGGGAGCCTGCTTGGGGGCCCAAGTCTGCTGGCATCCCCGCTCTGTGTGGCTCCATCC +>random_negative_2739 +TGGGAATAATCATTGACATGTCTCTTTTTTTTCTCCCAAGTGAACTTGAAGATGATTTACT +>random_negative_2160 +AGCTACTGAGGCAGAAGAATCGCTTGAACTTGGGAGGCGAAGGTCGCAGTGAGCCAAGATC +>random_negative_9685 +GAGAGGGAAGGAAAATTAACTCAGGGGGAGTGAATCTGTAGACCCACTTGAGATAAGATAC +>random_negative_3149 +TAGTGAGACCCTCATCTCTACAAAAAAATAAAAAAATTAGCTGGGCATGGCGGTGCACACC +>random_negative_21903 +TTTGGCACCCATGGTCACTTCACTGGCTTTCCATTTGGCTTCTCACCTGGGAAATACAAAA +>random_negative_152 +GATGGACTTATAGGTGTTGCTTGTGGCTGGGTGACTTGCTTCTGCCAACGAGATTTTCACA +>random_negative_14161 +GGAGGCCGAGGTGGGCGGATCATGAGGTCAAGAGATTGAGACCATTCTGGCCAACGTGGTG +>random_negative_3092 +CCTCTTCTAAGTTCCACTTCTGCCACTCCATGCCTCCCTATCCCCAAGCCTCCCTGTCTCC +>random_negative_8592 +TTTTAATCACTTGGGAAAGCAAACTGCTGGAGTGTTTGTGAGAGAGAAGTCAAATTTTGGT +>random_negative_5320 +TTTATAAGCCATATTCCGTGATGTAGATGAAATCTGTTTTCTCTCCTTGTTCATTGGAGAC +>random_negative_13676 +GTTGTACAAAAGTAATTTGCTGTGGTGTTTATGGTCATTATTGTTATAATTTAACCTTTCC +>random_negative_133 +TATAAACTTTAGATATGTAAAGAAACAGACAAATACTCATTTTAGTGTTGTTTGTATTCGC +>random_negative_1410 +TCAAAGCACCTAGTATGACATCTAGCCATAGTAGATGTCAATAAATATTAGCTCCCTTATG +>random_negative_21688 +AAAATTAGCCGGGCGTGGTGGCACACACCTGTAACCCCAGGTACTTGGGAGACTGAGGTGG +>random_negative_1620 +TCAAAGTGCTGGGATTACAGATATGAGCCGCCTTGCCCAGTGGCACTAATTTTAAGACAAA +>random_negative_5127 +CACAGTGAAACTCCGTCTCTACTAAAGAAAAATACAAAAAATTAGCCGGGCGTGGTGGCGG +>random_negative_14514 +TGAAGGGGCTCTGCAAATTGTTCTGCTTGACTCTGCATCGATATAGGTGAGTCCCAGCCAA +>random_negative_679 +ACTGAAGGAGTATATGCTTTGATATTTAGATGGCACAAATGTAAATTTTGGTGTGGGAAGA +>random_negative_19558 +CTGACAGAACTATCTTAAAATTTACTTAAATCAGTGTTCAATGTTTACATCAATTTTTTTT +>random_negative_9896 +TGTGATCATAGCTCACTGCAGCCTTGGAACTCCTGGGCTCAACTGATCCTCTTGCCTCAGC +>random_negative_7045 +ATTATTCCTCCCTCTGGAAGATTGATGCATTTCTTTCCCATCCGGGCTTCATCTTAGCCTC +>random_negative_8389 +GACTGTCTCAGCTGAAATATAGATTCCTTTTCAGTAAACTGATGCACAATTCACAAATAGC +>random_negative_952 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+GCCGTGATCTTCACCCTGGACGACACTGTGGCTGAGTTTGTGGCTGCTGTGTGGCACGGCT +>random_negative_13285 +GCCTCCTCGCGGCTCTAGGGCCGGCGCGGTGACGTGCGCGTGCGCGCACTGGAGGGAAAAG +>random_negative_11805 +TTGTGATCCACCCGTCTCGGCCTCCCAAAGTGCTGGGATTACAGGTGTGAGCCACCGTGCC +>random_negative_5801 +CAGAGGAGGCACATGGTGGCTTTGCCCCACACTGGGAAGCCTTCCCTGTTACTCTCTCCAT +>random_negative_2319 +AAAGAACTGGAGGCCAAGATGTTGGCCCAGAAGGCTGAGGAAAAGGAGAACCATTGTCCCA +>random_negative_13671 +GCAGTATAAGTTAAATTGGCTTCCTGGTTGACTCAACATTCCCATCCTATTCCCACCTGCT +>random_negative_8170 +AGCTGCTTGGGAGGCTGAGGTGGGAGGATCATTTGAGCCTGGGAGGTAGAAGTTGCAGTGA +>random_negative_18582 +GCGGCCACCGGCGAAGTTCTAGGGGCGGGGGGCTCGCCCCGCGCAGGAGTCACCCCAACTT +>random_negative_12868 +CTGATCTGAAATTTCCTTTTAGAGTTGGCCGTGGCCACCATAAAGTTATTTTGGTAGGAAA +>random_negative_19826 +TCACATCACGTCAGGAGACAGGTGAATACCACTTGGTCCCAATACTTGTGATGCTAAATTT +>random_negative_18497 +ATTATATTTGTCTTAAAAAAACTCTATAATTATTTAAAGAAGTCTTGCATTTATGTTGAAA +>random_negative_10829 +GATTACAGGTGTGTGCCACCATGCCTGGCTAATTTTTGTATTTTTAGTAGAGACGGGGTTT +>random_negative_1412 +ACACAGGTGCGGGGCCGGGGTGGTGCGCCCGGGGCCTGGGTGCAGGGGGCAGCGTGGGACA +>random_negative_11257 +ATTTAGTTTTCTAGAATGAGCTTGTGTCACTTTTAATAGAAAAAAACATTTTTTGATCTCC +>random_negative_20098 +ATAAATTATATATCAGACATGTAAAATTTAAAGTATCATTTGAAATCAAAACTTGTCTGAA +>random_negative_20240 +GAACCTGGGAGGCAGAGGTTGCAGCGAGCCAAGATTGTGCCACTGCACTCCAGCCTGGGCC +>random_negative_777 +TCCAGAGGCCGGCCTCACCTGTGCTGTTTGAGGAAAGATGGGCCTACCATGGTGCATGCCT +>random_negative_6525 +ATATTTTAAACCTTCACATTCCTCCATTTCACAGATAAAGAAATTGAGCCTGAGAGGCTAA +>random_negative_18690 +GTATATGGTATATGTATGTATATTGGGTATATGGTATGAGTATATGTATGTGTGTATATGG +>random_negative_12755 +TTCAGAGGCTGATGTCCCCTGGGTGCCCTGGGAGCTGTAGATGTCCTGCCAAGGAAGCGGT +>random_negative_10380 +AAGTTCTTCAAGTTCCGCCCCCCGCCCTCCCCGCCCCATCCCCTCCCCCCGCCCCCGACCC +>random_negative_20973 +GACCCTGAGCAGGGGTGGGGTCAGCCTGGCCTCGGGGATCTCCAGGGGGAGACCCTGAGTG +>random_negative_13740 +CTCACTGAAGGAATCGCTGAGGAGGGGAGGAAGCAGGCCATTTTCGGTATTGGGGGAAGAG +>random_negative_10204 +AGAGGCCAACCCTCAGACAAAAAAGAGATAAAGGCAGGCATGATGTTTCCAAAATACTTGA +>random_negative_11634 +TCCATTCATCAGTTTGGCAAATACTTTAAAAATATTCATACCCTTTGAATTACCAATTCTA +>random_negative_7619 +CATGATAACTCACTATCAAGAAAGCAGCATGGGGGTAGCCACCCCCATGATTCAAATTACC +>random_negative_11848 +TAAGCCGTTGCATCCTTTGTAGTATTGGTATGAAGTTGCTTCATCTTTTCTAGTATTGTCA +>random_negative_17833 +TGGAACAATCACTGTGGCCATGTGAATGCCACTGGCCACTTGGCTTAGTGGCTATTGTGGT +>random_negative_4737 +TGGGGCTGGTCAGCCAGAGGGTGGGACGTGTCCTGGTCCCGGCCTTTGTGGGGGAGGGGTG +>random_negative_5745 +CCTAGGTCAGCCTGAGGTTGGTTTGTCCTGGCCGCGGCAGCTCCTGCGCCCCTCCATTGTG +>random_negative_6377 +GGAAGGAGGAGCTCAGAGACCAGGCCTGGGGGTGGGTGGGAGGGGGAAACCCTGGGAAGGG +>random_negative_5126 +ACTCTGCCATACTTAGAATTAATCATTCTCAACTGTAAAGAGCACATTCAGCTCAGTGACT +>random_negative_10401 +TTGCCCAGGCAGGTCTGGAATTCCTTGGCTCAGGTGATCCTCCTGCCTCAGCCTCCCAAAG +>random_negative_2386 +CAGTTGTTAATTTTTTGTCTCCCTCCTTCCCTCCATAGAGCTCCAGTAGGGTATGCCCTTG +>random_negative_15781 +TATAATCCCAGCTACTCAGGAGACTGAGGCAGGAGAATTGCGTGAACCTGGGAGACAGAGG +>random_negative_3294 +GCTTCCAGCCTGCTGGCTTCCTGCTTGGGTGCCTCTGTCTAGGAAGACCTGCAGCAGCTGT +>random_negative_10785 +CCCTAGGTGGTGGTTAAAAGGACAAGTCCATAATGCAAGAATCTGTCAGGCTGCGCATTTA +>random_negative_22515 +CCAGAACCTAAAATAAAAGAAAAAGAAAAAAAGGGAAGCAGAGCATAAAAGTTTGGAAAAT +>random_negative_4650 +AGATGGGATCTCCCTGTGTTGCCCAGGCTAGTCTTGGACTCCTGGGCTCAAACAGTCCTCC +>random_negative_8905 +AGCTCACTGCAACCTCTACTTCCCTGGCTTAAACCATCCTCCCACCTCAGCCTCCTGAGTA +>random_negative_1900 +ATGGCCTGCCTGAGGCTGATGGGAAAGTCAAGGGCAGGGGCCTCAGGGAAAAAAAACCAAT +>random_negative_10198 +TGACAGCACGGCCTGTCTCATTTAATAGGTGACAAAGATCGTGTCCTTTCACCTGCCACTT +>random_negative_21641 +GTGCATTTTCCTAAGTTACCTTGTCTAATTTGCTATTCCTAGTTGATGTCTCAGGAACATC +>random_negative_11505 +GAGCCTTGTCCCAGGTGCTGATAAGTCCTCATGCACTTACTGAGTGCCTCCTCTGTGCGGG +>random_negative_18523 +GTGGCGTTGCTCTCCTTATCGTTAAGGGAACCTTGCTCCTGGCACCTTTGGCCCAATAGGT +>random_negative_21183 +AGAGTGGAAACAGGAGGTCTTGGGAAAATGAAATACAATTAGAATTTAAATTTTAAAAAAT +>random_negative_11834 +GGGGCTTCTTGCTTTTGAATACATTTCCAGAAGGAAATTACTGGGTCAGAGGATAAGAACA +>random_negative_13865 +TAGTAGGCATGAATACCTTGTTAAGAATCTGGGCCTTCATGTAAAAAAGATTCTCTACAGA +>random_negative_8488 +TTTCTCGGGACAGAAGTGGCCTTACTGGATCCCCCCCCCCGCCCCATAGGTTTGTTTTGAA +>random_negative_21092 +CCTTGACCTCTAAGGGATAGGATTGCATCCTGCTGTGGGTTTTCGAATCTCTCCCCTACCT +>random_negative_16418 +ACTTTGGCCTCCCAAAGTGTTGGAATTACAGGTGTGAGCCACCACACCCAGCAGGAAAAGT +>random_negative_10844 +TTGCCCAGGCTGGAGTGCATTGGCATGATCTTGGCTCACTACAACCTCTGCCGCCCGGGTT +>random_negative_6689 +AGCTTTCAGGGAATCAGTTCTCAACTTTATAATTTGTAAACCTTTTTTTTTTTTTAACTTC +>random_negative_14497 +GTAATTCCAGCTACTCAGGAGGCTGAGGCATGAGAATCGCTTGAACCTGGGAGGCAGAGGT +>random_negative_17576 +TCTGCTGAAAATACAAAAATTAGCTGGGCATGGTGGTGCGTGCCTGTAGTCCCAGCTACTC +>random_negative_18413 +CCTCAGCCATCTACCCCTCCAGACCAGCCCCACCGTAGACCCCTAGCCCATCTTAGACCTC +>random_negative_6585 +CCTTCAGGCTGGGGTGTCAGGAGCTTTGAGAGGGGCACAACCAGAGCCCTGGGGGCCCTCA +>random_negative_1238 +GAATCTCAGGGCAGAAGGGACTTGGGGAGAACTGGGGTCCATTTCTTTCTTCTTCCAATAA +>random_negative_13668 +AAAAGGAATTGAACATGGATACTATACTATCTAATACATAAATTTGTCCAGTTGTCCAAAA +>random_negative_14698 +GGATTTGCTTTGCTGTGCCATTGGGGTACAGCTGCTGCTCTTACTCTAGACCAAAAAGTCG +>random_negative_18706 +GCCATAGTTATGACCTGCTTCATCCGGTAACTCAGAAGGTTTCAAAGGTCCTCTGGGCCAG +>random_negative_175 +TAAGCTCCTGTTCTAGGGAAGACAGAAAGAAAATACACGTGTCCTTAGTATATTAGAAGAT +>random_negative_4645 +GCCGGGCGCGATGGCTCACACTTGTAATCCCAGCACTTTGGGAGGCTGAGGTGGGCGGATT +>random_negative_17038 +AGAGAGCAAGAGGACGTAGAGCAGGGGGCAGGGTGTCTCACCCCGTCTTCCGCACAGACCC +>random_negative_15701 +TAGGTTAAAGTTTTTGGATGTGTAATGATATTCCATGATACTCCAAGTACTTCTCCAGAGT +>random_negative_20916 +GATAATATTTGAAGGTAGAGCCGGCAGGAGTTGTAACATGAAGGCTGCACCTGCAGGGTTT +>random_negative_18500 +TAAATGTGTCCCAGAGATTCTGGTATGTTTCTTTGTTCTCATTGGTTTCAAAGAACATCTT +>random_negative_14366 +ATCTAGAGAGCAGCAAGGCTAGGTTCAGGTGCTGCTGGCTGTGCCAGGGCAGCCTGGCATC +>random_negative_14477 +GGCCAGGAGAGGGCCCAACCTCTGACCCCTTGCAGCTGTGATCCGGAACTATGGGAACCTC +>random_negative_4731 +GAGTGATCTCGGCAGTCTGGGTGGGTGGGAGGGGCGTCGTCGGCACTGTGGGGTCCGCCCG +>random_negative_17203 +TTGATCACAGCCAGTGATCATAATCATTCAATATACCCTATTTCATTTTTGACAAGCTTTT +>random_negative_18005 +TGGGCCCCCAGCAGAGCCACCATGCAAAGTGGTCAGTGATGCTTCAGGGCAGCACACAGCA +>random_negative_11591 +CGGGAGGCAGAGGTTGCAGTGAGCCGAGATGGTGCCATTGCACTCCAGCCTGGGTAACAAG +>random_negative_2259 +CCGCCTCGGGGACCGGGAAACTGAGGCTCGGGCGGCCTGAGACGCCGTCAAGGTCATGTAG +>random_negative_14068 +ACAGACAGGACTTAGGAGATAAAACAAGTTTGGGACAAATTAAGAAATGGAATGTTGAATG +>random_negative_9620 +GGGGTTCCCACTTCTGAACCAGTAGATAGCAGAGAAAGAAAGGTGGCATATCCAGGGTTCT +>random_negative_20085 +AAAAAAAAACCAAAAAAATTAAAAGGGAGAGAGAGGAGGAAAAAAGAGGGAAAGGAAAGAG +>random_negative_21085 +GGTGGTAGAGAAGTCTGAAGAACCCGCAGGCCAAATCCTGTCTCATTTGTCTTCAGAACTT +>random_negative_1929 +GTGCTTTCGAATGCCTCCCCCCAACTTTTTTTCATTGTTGTTGTTGAGATGGAGTCTTGCT +>random_negative_19302 +ATGGTGGCTGCAGTTTGGGCTGCGGGTGGAAGGGGAGTTACGGGAGCTGAGTCAGGAAGAC +>random_negative_20522 +TTAGAGAATATAGCTAGGCTGCTACTGGATTAGCTATACTTATAACATTCTCACCTCTCTA +>random_negative_14784 +TAAAAACATTCTTAACTATTTTATAAGTAAAATCTTTCCTTGAGGCTATTACCTGAAGCCT +>random_negative_12356 +AGGGCACCGCTGGCCTCCAGGGGGTGTTCGGAAATGCTGAGGAGGGAGGATTAACTGTCTT +>random_negative_9216 +CTGATACCAAAAACAAATGAAGACAGTACAAGAAAACTACAGACCAATATCTCCAATGAAT +>random_negative_14501 +TCCTTTTTGAGACGGAGTCTCGCTCTGTCACCCAGGCTGGAGTGCAGTGGCATGATCTCGG +>random_negative_18578 +TCAGCGGATCTGCCTGCCTCAGCCTCCCAAAGCGCTGAGATTACAGGCATGAGCCACTCCG +>random_negative_1015 +TCAGGCATGGCTGGATCCAGGGATTCAAGCAGCAAAGTGAGGGCCTTGTGTTTCCATCTCT +>random_negative_22950 +GTGATCTCACTTAGCTCACTGCAACCTCTGCCTCCCGACTTCAAGCAATTCTCCTGCCTCA +>random_negative_13679 +AAAAAAAAAAAAAAAAAAAAAAGAATACAACTGTGGTTACCAACTTTAAGGTAGGACCAGG +>random_negative_13573 +TAAAAATAAAAAAATTAGCTGGGCATGGTGACACACAAGTGTAGTCCCAGCTACTCAGGAG +>random_negative_17615 +GGCACTGAGGCTGCTGTGAGATCCAGCGAACGGGAGGGTTGGGTTTTCTGAGGCCACGTGG +>random_negative_9657 +GCTTAAAAATATCCAGTAGTAATACCTTTGACTTTCTGTTAACACTTCGTTTATTTTTATT +>random_negative_21497 +TTTGTGATCCTCCTGCCTCAGCCTCCTGAGTAGCTGGGACTCCAGGTGCATGCCACCATGC +>random_negative_18617 +AATACAAAAATTAGCCAGGTATGGTGGTGTGTGCCTGTAATCCCAGCTACTTGGGAGGCTG +>random_negative_3943 +AGTGTCTTATTTCATCACTTAGCAGAGCTAACTGCAGAGCGTTAGTGGGTAAATACATTTC +>random_negative_10308 +ATGTTTCTCCATACCCTTCTTCCATATCTCATACCTAATGAATTATATATGTAGCTCAGAT +>random_negative_1608 +ATGAGTCCCACGTGTGCCCCGACCCACTCATGCAGTGACAGCTCCCCAGTGGCGGCCGGCC +>random_negative_13652 +AATTGCTTGAACCCGGGAAGAGGAGGTTGCGGTGAGGCGAGATCGCGCCATTATACTCCAG +>random_negative_19418 +TAGGGGATAAATTGCTTGTCGAAACTGTGCTGGGTGTGCCTGTCTGACACCTGATCTTGCA +>random_negative_16400 +TTATTTTTTTGAGACAGAGTCTCGCTCTGTCACCCAGGCTGGAGTGCAGTGGCGCAATCTC +>random_negative_13021 +GATATACATGATACCTTCTGGAAGCATGTATACTAAATTGTTTACAGTGACATCTTCTGTG +>random_negative_2619 +TGGAGGAAAAACAGATATACAAGTATCAAGAGTAGTTACGTAAGGGTGATTCTTTTTGTTC +>random_negative_14317 +GAATTTTAAAATTCACCGAATTTTTCATCATTAGGAAAATCCATAATTATGAATGAGCACA +>random_negative_22811 +GTATGGCCTCACTGTGCCCATTTCCCAACCTTTGTTGGTCTCCACCCATAGGTGGGGTAAG +>random_negative_23062 +GCGATTTGCAGATATTTTCTGCTGGTCTGTAGCTCGTGTGTATTCACTTAACAGCTTCTTT +>random_negative_22541 +CTCAGCCTTCCGAGTAGCTGGGACTACAGGCACCCACCACCACGCCCGGCTAATTTTTTGT +>random_negative_5737 +CTCAGGTGATCCCAAAGTGCTGGGCCTTGGCCTCCCAAGGTGCTGGGATTACAGGCATGAG +>random_negative_1673 +GTCCTGTGTATGTAGTAGGAACTGTTATTATCTACATTTTACAGGAGAGAAAAGGCTGAGG +>random_negative_230 +CTCAAGGGAGAAGCTTGGGGAGCCCCAGAGTTCTGTGCAAACATCCCTGAAGCTTCAAGAT +>random_negative_9802 +TTTTTTTTTTTTTTTGAGATGGAGTTTTGCTCCTATCACCCAGGCTGGAGTGCAATGGCGC +>random_negative_9955 +TTAAATGCTGTCTGAGAGTTGGGGCAGGCGCTGTCTCCCCAGGACTGGCATGGGCAGGAAT +>random_negative_22802 +GAAGAGAGTTCTGAAAAAGGATGACAAGTAGAAAGTAATATAATTTCTGTTAGTATTAATT +>random_negative_20602 +TACAGTGAGATACCACTTTACAGATGCTTAGACTGGCAAAAATTAAAATGTTGGAGAAGAT +>random_negative_3648 +GGATGGGTTAATTTAATTTAGGTTAATTTAAAAGTATGAGTTTTGGAGTTCAGGTGGGCCT +>random_negative_10295 +TAAGACATCAGCAGAAAAGTACTGCTTTCAGCCCTGGTTGGAGGTGAATGGTTTCTGTGCT +>random_negative_9912 +AACAGACACAGCCCTTCTTGGCATTCAAAGTTGCACCCTGATGCCTGTGAGGGAGTCGTGA +>random_negative_3065 +CAATAGAATTCTTACTGAACAATCTGGAGTAGAAGTAATAAAAAGAACAATTATGTATTCC +>random_negative_8553 +TATACATAGAACCAAGAATCGATAGGATGCAGGGCTGCTTGATTGTACCAGAAACAAAACA +>random_negative_3544 +CATAGCGTCAATGTTGACCTATTTGATATATTTTTAAGTTGCAGATTATAGATGCAGAAAG +>random_negative_11427 +CCACTGAGAAAGAGTCAGGCCTTTCTTTTTTTTCTTTTCTTTTCTTTTCTTTTTTTGAGAT +>random_negative_19235 +AAAGGAATAAGAACAATGAGCCATTCATGAGGTTGGGGCAGGGGACATAGTGACAGAAACC +>random_negative_20451 +GCATTATAAAAACATCCCTCCAGCCTTTTACCTTCTACTATGGATTGTACTGAAAGTTTTA +>random_negative_11094 +GGGCCCCAGAAACCCAGAGGCAAGAGGCAGGTGCTCCATCAGCTTGGCCTGATGCTTGCCT +>random_negative_1935 +AGAGGTGGGAAATCATTAAACAAAAGAAAGTCTTAAATTTTTTTTTGTAATTGGGTGCCTT +>random_negative_4668 +AAAAGCTAAGCAGACTTTTTCGGATTACATTGGTCATTGAGAATTTCAGTGATGGGGGAAT +>random_negative_16729 +AAATTTTATCCCTGAGAAGCAGGGAGAAGGAAGTAATGATGATATGAAGTTTTAATGGCTC +>random_negative_17377 +GTTTGCAGATGACATGATTGTATATCTAGAAAATCCCATTGTCTCAGCCCAAAATCTCCTT +>random_negative_20594 +GCGGCTGGCCGGGCGGAGGCGCCCCCCCACCTCCTTCCCGGACGGGGCGGCTGGCCGGGCG +>random_negative_20088 +GTAATCATACCTTCCATATGTGAAGGGCTAGTTTTCCAGAGTTTTTATTTCTTGGTGTTAG +>random_negative_19249 +TCTCTCTCTCTCTCTCTCTCTCTCTCACACACACACACACACACACACACACACACACACA +>random_negative_863 +GAAATGAGGTTGGAATTTCGAGGTTTTGAGCAGGGGGAGCATCTTATATTCACCCTTAAAT +>random_negative_4635 +AAGTCCTTAAAAGAATAACTCTGATATCTAGAAATTATTAAGAACTGCTCATTCGCTTAGC +>random_negative_19233 +GTGATAGTTGCTGCTTGAGGTTTATTGCTGATGACAAAGTGTGGGCTATTTAGGGTTTCTA +>random_negative_16639 +CTCTCAAAGTGTTAGGATTTCAGGCATAAACAACTGAGTCCAGCCTATTCTCTTCAGGTAT +>random_negative_19843 +AAAAGAAACACCAGGAGTGAACTCTGATGCAAACCATGGACTTTCGGTGGGGATGATGGGT +>random_negative_19142 +CTACACCCCTGCAAAGTCAGATTGCATATCATTATGAGATAAGATGTCTTCTGAGTTTTGA +>random_negative_13036 +AGTAACTGCTAGTATTGCTTGGTGCCATTGCTTCAGTTTGTGCCCCAGGGTTCACATTGCA +>random_negative_1524 +GTTTGCTTCTTGTTTTAAGCATGGCTCCAGAAATACCCGTCTCTGTGAGAAACCCACCCTC +>random_negative_2396 +TGTTTGCTATTGTGTGTGTTTTAGGTTTGCTGTTGTTGTTGTTTTAGAGACAGGGTATAGC +>random_negative_3985 +TGGGAATGGAGCCTGGGCCTCTCCGGTGGGCTGAGTAAGAGTCTTGCCGCTGGTACCCAGG +>random_negative_17024 +CTTTGTTGCTTATGATTTTGGTATCATAGCTAAGAAATCCAAGATCACAAAGATTTACACC +>random_negative_23290 +AAAGCACTTTCATGTTTACCTCATTTGATTTTCACAGCAACTGTGTGGGGAGAATCATCCC +>random_negative_3396 +AGCAAACCAGAGCTCACGGAGCTTAAGGAACCTGCCCAGAGCCACACAGCCCCAGCCACGG +>random_negative_5378 +CTAGTTTGTTTCTAAAGCCCATGTAATTCCAATGCTCTTGGAGCATTTTCTTCCTTAAAAT +>random_negative_18019 +TCATTTGAGGTCAAGAGTTCGAGACCAGCCTGGCTAACATGGTGAAACCCCGTCTTTGCTA +>random_negative_13977 +AGATGGATCTTTGTCCCTCTGCAACCCTTAGGATTAAGGGTTCTCTTATAAAAGACAAGGG +>random_negative_14258 +TATGGGTTTCAGACTTGGGCATTATATGTTCTTTTGCTTAAAAAAAAGTGCAGTTATCTTT +>random_negative_18041 +TGGGGTACTATGCTGTATTAATTCATTTTCACATTGCTGTAAAGAAATAATGGTTCTGCAG +>random_negative_19148 +GTGCTGATGACTTATCCTTTTCTCCCTTAAGAAAGAGTAAATGTTTTTGCTTGGATTGAGT +>random_negative_23331 +ACGCTGAGGGCATCGTGGGTTGTCACCCAGGAGACCTGCTCTGGCTCCTTGACTTGGGTTT +>random_negative_5095 +AACAATTCCCCGCAGCCTCAGAATGTCGTGTTTGATGTTCAGATCCCCAAAGGAGCATTCA +>random_negative_17023 +CCACCACGCCCAGCTAATGATTATTTTTTTTAGGGCAAGGACTCGCTATGTGGCCCAGGCT +>random_negative_3553 +ACTTATGCCCAGGACCCCACCCCAGATTTATTCAATTAGAATCTTCAGGAGGCAGACCCTG +>random_negative_6768 +ACTGTGCTTGGAAAGGCAGGTTCTGTTTGTGGACCTAGGCCTGCTGGTGTTCTGCCTGTTC +>random_negative_19638 +GGTGTGAGCAATCTCTGGGCTGTAGGAAAATGCTTCTGCAGCCTCAGCTGCGCCTCCACTT +>random_negative_8269 +AGGCAGGAGAATCGCTTGAACCTAGGACGCAGAGGTTGCAGTGAGCCAAGATGACACCATT +>random_negative_19286 +CCACTGCACTCTAGCCTGGGTGACAGAGCAAGACCTGGTCTCAAAAAAAAAAAAAATGTCC +>random_negative_22467 +GTTCTGAAGAGCTGTTGTCCACCCAGGCGGGCTGCGTGCACTTCCCCCACACGGCGCCCTG +>random_negative_21612 +TCTAGGCTTTTTTTGTTTGTTTTTTTTGTTTTTTGTTTTTTTTTTTTTGAGGCAGTCTCTC +>random_negative_11100 +ATCGTGTACCGCTGTGTGGACTACATCACGCAGTGCGGTGAGCCCTGCCCCTAGGGTGCCA +>random_negative_6378 +GAGTGATCTGCACGGCACTTTATGCCTGGGGGCTGCTGTGGATCTGGACGAGACCTTGTCC +>random_negative_23121 +TTCTCAAACCCACTCAGCCTTCATCGCTGACACACACACTCCTACCCCAACCAGACTAAAT +>random_negative_100 +GGTTGCCTGTAAATTACAGAACTGGATCTCAACTAGAGATATATCATAAAACTCCTGTACT +>random_negative_4844 +CTTCATTCCCATAATTGCTCTGTGTCATCTGTGATTGCGTTTTTATAATTTCTTCTTGGAT +>random_negative_22868 +AGTTGAAAGGAACCTTAATTGGTTTGTTGTTTGTTTCTTTCTTTGTTTTGAGATCTGGTCT +>random_negative_22586 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+GACCTCTGTTGGGGCTCAGGACAGAGAGGGGATGGAGATGCGGGTGGAGGCCTGTCTCTCC +>random_negative_13890 +TTATAAAGAAACTGTTGACAATTTTGTGGTCCCCTCAGTCTCTGAGACTTCAGTACCAAAT +>random_negative_658 +TCATGCTCGTGTTAAATATTATCACTGTTAGTCTGATAAGTGTCATCAGATTAGCATGATA +>random_negative_8661 +CAAGTAATAGTGGAGGTCTTATTCTTTCCATTCCTAGTTCTCAGTATCTCCATCGTGACTC +>random_negative_18153 +TTAATAGCATGTTCTATGCATGTTCTGCACAGTTATCTTTTTACTTGCTCTGATTTGGAGA +>random_negative_21184 +TTTTTGTTTTTGTGCCAGAGTCTCGCTCTGTCTCCCAGGCTGGAGTGCAGTGGCATGACTG +>random_negative_11061 +CAGGTGCACGCAGGATGGAGAGGCACGTTTTGCAGTTCCTGCAAAAGTGCCCTGAGGCCCG +>random_negative_3609 +CATTGGCCAGGCTGGTCTCAAACTCCTGATCTCAGGTGATTTCCCTGCCTTAGCCTCCCAA +>random_negative_18590 +CTACTCGGGAGGCTAAGGCAGGAGAATCTCTTGAACACAGGAGGTGGAGGTTTCAGTGAGC +>random_negative_11265 +ATGATCTTGAAGGGGCTAATTACCATACGGTAGGGGCATCTCTGTATAGGGAAAAGTTATA +>random_negative_9883 +GTACATACATATGCTCATTTATGTACATACATGTGCATATACGCATGGAAAAATAAACACA +>random_negative_829 +ACACTCAGGACAGTCAAACCCTCCCATAATTCAGTATCTCACACAAACCTGTGTTTACAAA +>random_negative_1338 +CCTCGGGGGTGCCGGCATGGAGCGCATGGGCGCGGGCCTGGGCCACGGCATGGATCGCGTG +>random_negative_6364 +AGTTTGGGAAGAGTTGGCCTTTAACGTTAAAAACAGTTCCATGGTGTTTACTGTAGGCCAA +>random_negative_6684 +TGGCTTGGTCGTTCCCCCTTTGTCCCCGCCATCCGGCGGAGGGGACGGGAGGGGGTGGTTT +>random_negative_6088 +CCGAAACCCTGACTTTCTCCTCCACATCATCCAGCGGCAGGTGAGTGCCGAGGCTCCAGGA +>random_negative_19828 +TGAAATGTTAAAAACATGAAGTTATACAAGCATTGAAAGAAAGTATAACTGCATGGTTGTA +>random_negative_11262 +CTATTCATGAGTGAGATACTCTCATGTAATGTACTGTCTCACACACATTTATTATTTCATA +>random_negative_9654 +CCCATGTATGCAAGTAAAGACACCAAACATTCTTTAAATGCTGCTTTTAAACTTTGAAAGT +>random_negative_1366 +GAGTGGTGGGGAACAGGTGTGCTTAGCTAGATGATGGTGGCTCAGCCAGTTAAAGGGCAAG +>random_negative_8318 +TGGGCGCGAGGCTGGTCTGACCGCGTGGCTGGGCCTGGAGCTGGCTTGTAACTAGCTGGGC +>random_negative_13940 +TAAAGGTGAGAACCTGTGAAGGATATGGAGATAATCAGGAATGGAATAGACAGGTGATGAT +>random_negative_13933 +AGTTCCTGCTGTTCCTTCTGCTTGGAAGATCTTGACACTGCTCTGCCAAGCGAACTTCTCT +>random_negative_14370 +CTGTGAAGGTGAGATGGAGTCGCCGAAAAGATTCAAAGCAAGTCTCAGCAAGCTGCCTTTT +>random_negative_15259 +AAAGCACAACTTTTGTTGCTTAGGACTTTGCATCAACTGTTGTTCCAGACCTCACTTCAAC +>random_negative_13562 +TGAACCTGGGAGATGGAGTTTGCAGTGAGCCAAGATGTAGTTGCTGCACTCCAGCCTGGGC +>random_negative_3410 +TGGGAGGTAGTAAGGAGTGATTGCATTTCGGGGATATTTTGAAGGTATTGCTGAGCAGGAT +>random_negative_21537 +AACCTTGTCCCCCTGTCCGGCCCAGAGGTGCCCCCACCCCCGAGGACCCTGCTGGAGGCGC +>random_negative_21371 +CTCAGAGGCTGAGGAAAGTGGTAGGCTGTGGCCATGGTCAGGAGGGGTCAAGATAAATTCC +>random_negative_19887 +CAGGATTTAGGAGGTAGGCAAGTCACCCTAGCCAAGTCATAAGCCCATGGCTCAATTGCCT +>random_negative_17780 +ACTTAACCAGCTATGTGACTGTGCAATTTACCAACCTCTCAGGGCCACATTTTTTCATCTG +>random_negative_13424 +ATTAAACTGAGGGAAGGCCAAAGACCTGGTATGAAAGTGAGAGAAGGCCGAAGACCTGGTA +>random_negative_17379 +GACCTGGGGTCAGCAAACTGCTGGCATCTTGGCAGCTTGGAATGGCCAGTTGGTGTTCCTC +>random_negative_15369 +AAGCTTCCACAGCGTGGAAGGGTACCCGAGCAGGTTGCCGCTGCTGGACGTTGGGGGGTGT +>random_negative_16757 +CACTGCAACCTCTGCCTCCCAGGTTCAAGGGATTCTCCTGCCTCAGCCTCCAGAGTAGCTG +>random_negative_3630 +CCAGTTTCAGGATATCTTTCTGATATCCCAGGTCTGCATTCAGGCCCCTCCTGTCATGTCT +>random_negative_5540 +GCCGCTGTAGGCACACAGAGGGCAAAACGATGGAAAGCCCTGCCCTCGTTCTAGTCAGGCC +>random_negative_22168 +CTTGCTGGAGGGGCTGGATGGGACTGTTCCAGCCCCCTCCCAACCCACCCCATTTGCACAC +>random_negative_4381 +GGCTGGGGCCTTCTTTTTTTTTTTTTGAAACCGAGTCTTACTCTGTCTCCCAGGCTGGAGT +>random_negative_3971 +TGAGGAGCATCTGTACATCAAAATTTTATTGGTAACTTTGCCCAAAGGGGGTGGGATTGTG +>random_negative_10508 +TTAGCATTGTGCATGTTTAGAAAAGTGCTTCACTTTCAAGTGAATTAAGTATCTCAGGAGG +>random_negative_5558 +CGAGCGCTTCCTGCGCGAGGCCCTCCCTGGGAATAGGAAGCGGGAGAGGCTGGAGATGTTT +>random_negative_934 +CTGACCCTGCTCTCCCCCAGCTCCTGGCCTGCGTCTTCGTGGAGCAGATGCAGACCGGCTT +>random_negative_22146 +GAGAGAGCCCCTGGTACTTGGTCCTAGATAAACCTCTGGGTCTCAGTTCTATTGTGTCGTC +>random_negative_132 +TTCCCTCTTGTTGCCCAGGCATGATCTTGGCTCACCGCAACCTCCGCCTCCCGGGTTCAGG +>random_negative_13073 +TAAGAAGCCTCTTAGCAGATTTCTTTTTTTTTTGAGATGGAGTCTCGCTCTGTTGCCCAGG +>random_negative_22237 +GGTTGGGGATGGCTGCTTCCTTCCGGGCAGCTCAGACAGGGCCCGGCTCAGCATCTGCTGC +>random_negative_20588 +TGCAGTGGCACAGTCTTGGCTCACTGCAGCTTCCGCCTCTTGGGTTCAAGCGATTCGCATG +>random_negative_20684 +TTTAATTGTTTTGTAGAGATGGATTTGCACCGGGTTGCTCAGGCTTCGTTGTGCTTTTGAT +>random_negative_19576 +GTGTGCCTTGTAGTCCCAGCTGCTCGGGAGGCTGAGGTGGGAGTATCTATTGAACCTGGGA +>random_negative_13688 +CACAGGGATGCAGTGGCACCTACCTGCGGACACTGTGTGGGCCGAGCACTGTAAGGCTTGG +>random_negative_15135 +CTGCAGAGCACACCAGAGACCGAAACATATTACTGCTTTGTAAACTTCTCAATATTTGCAC +>random_negative_16885 +TGGTGTGAATGGAGTGTTTCTTGGCTCTTTTTTCCCCGTTGTTTGGCAATTTTGGGTAGAA +>random_negative_19565 +TAATTTATTTCTTCATTCATTTATTCAACATACATTTTTTGAATCCTTAGAATAGGCCAAT +>random_negative_19809 +TTTTTTTTTTTTTTTTTTAAACTACATGGGGAAATCAACTAAGGGTGTAGAGATGCAAGTT +>random_negative_16706 +CAGCTACTTGGGAGGTTGAGGCAGAATAATCGTTTGAACCTGAGAGGCGGAGGTTGCAGTG +>random_negative_9304 +CTGGTGCCAGCCATGACTCTCACCTTACAAAGAGAGCAACCCTTTGTGAGATGCAGAGCAT +>random_negative_18927 +CCGGCTGCGCCTGGTCCGCAAGGGCAATGAGCAGCACGCCTTTACCCGCTGCTTCCACGCC +>random_negative_19431 +CAGAGCGAGACTGCATCTCAAAAAAAAGATGAAGGTAAAATAAGGTCATGTGGGTAGGCCC +>random_negative_21614 +GAGGCCTTCCTCAGGTAGCACCCCCTGGGCCCGGGCCCCTTCTCGCGGCCACCCCCAGGGC +>random_negative_6766 +GAAAACGGTGACTGGCTATCAAAGGGTAAGGATCCTCATGATGGAACTGTTCTGTATCTTG +>random_negative_20728 +CACTTGGCTGCTGTTGAGGAAAGGAAGATCAAATCTTTGGTGGCCCTGCTGGTGGAGACCC +>random_negative_14045 +TCCCAGCACTTTGGGAGGCTGAGGCAGGTGGATCACGAGGTCAAGAGATCGAGACCATCCT +>random_negative_21338 +TGCCCTATCTCCCTTTGGACCCCTTCTAGGGGTTATGTTGGATTTGGAAGCCACGAGGAGG +>random_negative_13954 +CACTACTGGGTATATATCCAAATTAAATGAAATCAAGTTCTCAAAGAGATATTAGCACTCT +>random_negative_15428 +CCATTTTTACAAAATGAAGGAAGTGGGTTCTGTCCCGTAGGGTTGAGGAGCCGAGATGCGG +>random_negative_9909 +CATTCCTCCAATGAAATACGAGGGCTTGTGCAACAGGCTTCTTATCTCATCTCCACCTGAT +>random_negative_636 +TCTAGCACTTCTTTTTTTAAAAGGTGAAAGAACAAATCTTTGTGATTGTTTCGGGGACCAC +>random_negative_20886 +TAAATCCAGGAATGAGCCCTTTGCAAACATAGGTGGGGAGGCGAGGAGGCTTTCAGCAGGA +>random_negative_5331 +TCTCATCATAGTTTCATTACTGCTGTTGTTTTAAAGATTGGGTGACATTGGGTGTATTTGA +>random_negative_1647 +GGGGTAAACACATTTATTTAGTAGCATCTTGACTAATAACAATTTCCTTGATCTAAACCTC +>random_negative_17516 +TGTCACAGAATAATGTAAAATTTAAAAACAGAAAAATATCAGCCTAATACTAGTGTAATCT +>random_negative_20589 +CAGCCCCAAGGACTTCTTAGCAGAGCAGGGCCCTTAGTGCATCTGGGTGGGCCCAGAGCAG +>random_negative_6858 +AGTCAGGGGATTCATGCTAGAAGCCAGAGATCATGATAAAGATAAGTAGAAGCCAATTAGA +>random_negative_16765 +GCCTGGGCGACAGAGCAAGACTCCATCTCAAAAAAAAACCAAACAAACCAACCAGGAGGCG +>random_negative_18794 +CAATACACAGACACCAGCATCATCAGCATCCGGAGGGACACAGGGTTGTTCCATCCAAAGC +>random_negative_22559 +CTGTTCTTTGGCCCTGGTAGGCGAGGCTGGCCAGGAGGCAGGGGCTCTTGTCTTCCAGTGC +>random_negative_5980 +TTTCTTCAGTTCTAAAACATACACAGGAAAAAACCAAATTGCATAGAAAGGCATAAACAGG +>random_negative_6981 +GGCTCTTTCCCATTTCCTGTCTTACCTATTCCTTCCCAGCATCAGGATGGAGGTGGGATGG +>random_negative_4243 +GAGGGCCATACCCTGAGGGAGGGAAGGGATCTTCAGGGTTGGAAGAGTGACACCTTTGCTC +>random_negative_7053 +TCCCTCTAATGTCAAGGCTAAGAGTATGCAATAAATCTAGTCATGGGTTATATGTAAGTAA +>random_negative_792 +TCTTAAACATACTCTTACTGTTCTGTCTTTATGAATCTGAACACTTAGATGATACTGCATT +>random_negative_11840 +GTGTTTTTATTTTCATTCAGTTCAAAATACTTTCTGATTTCCCATTTCATTTCTTCTTTGA +>random_negative_1330 +TGTTGGAGCACTTCAATCTTAATAAACATTTGCTCTGCCGTAACTGTGCCAAAGATAATAA +>random_negative_1411 +TGTGTGCCAACTTCTGCTCCCTCCAGCTCCCTGATGGGCTTTTCAGCACATCCAGGACCTG +>random_negative_8472 +TGGGCTCAGGGCTGAGAACTTGGGCACTGGAGCCCACGTTCTCAAAAACTCAGGATTTTTA +>random_negative_17832 +GAGGTGAGTGCCCGGGAGGGAAGCTGTGCGGGCAGCAGTCCTGGTTTACTCTCTTGAGCCT +>random_negative_10351 +GGAAAAGAGCAATGGAACACAGTATTTGCTAGCCTTCCTCATCATAGAGTCTATCTTTGTG +>random_negative_16697 +GCAGAGGTTGCAGTGAGCCGAGATCACGCCACTGCACTCCAGCCTGGGCAACAAGAGTGAA +>random_negative_4848 +TGATTGCTGTTGCCCTGTTTCCTGCTGCTTTGTTGTTCTGCCTGTCCTAGTCTCCTTTGAA +>random_negative_4543 +ACACACAAAAAGATGGCATTTGATATATGGCACACAGGGTACACTAATGAGACTTCCAGTT +>random_negative_298 +CTCAGCCTCCCAAAGTGCTGGGATTACAGGCGAGAGCCACCACGCCTGGCATAAAACTTTA +>random_negative_19437 +TGGGTGTCACCCTTGGGTGGCCTCGGAATCTAATCTCCGTTCTGCACTCGTTTGCATTGTG +>random_negative_18625 +TTCTGGAATCATCCCTTGGAACATGAGAATGGCAGATCTAGAAACTAGTTATTGAGAGTTT +>random_negative_11812 +TTTTTGAGACGGTGTCTCACTCTGTTGTCCAGGCTGGAGTGCAGTGGCGCGAGCTCGACTC +>random_negative_9925 +GCAAAGCTGGACATGTAATAAGACTAAGTAAACCTTAGCAGTAATTCTAGTTGTAGTTGGC +>random_negative_9922 +GCAGTGGCGCGATCTCAGCTCACTGCAACCTCTGCCTCCCGGGTTCACACCATTTTCCTGC +>random_negative_18673 +GAGGGTAGGGAATATGGTTGTGGCTAAACTATTCTCTGTGGTTTTATTGCCAGGGAATTGA +>random_negative_14402 +CTCCCAACCTCAGTTGATCCACCCACCTCTGCCTCCCAAAGTGTTAGGATTACAGGCGTGA +>random_negative_21020 +TGAGACCCTGTCTCAGATAAATAAATAGTATCAAAATAAGGAGCCAGGATAGTTGTGTGTG +>random_negative_19109 +AACAAAGCCATAGCAGAGCAAGTGATTTGCCCAAGCAAGTGTACACACATATATTTGAAAG +>random_negative_14890 +GTCTGCAACTGCAGTGCACACTGTCACTCGGTTAGAAGCTGGGGCTTAAGCATGGATCACT +>random_negative_11872 +GAAGAAGCTGCAGGAATACCGGGTCTTAATTACCACCCTCATCACTGCCGGCAGGTGGGGA +>random_negative_15637 +GAGATGCCATCTCAAAAAAAAATATATATATATATATTTTTTAAAAAAAGAATGTTTATCC +>random_negative_17237 +CAGCCCTTCTGAACCTGCCCCAGCCCCTCTGAACCTGGCCTGGGGCCCTGTTCTTGAGGCG +>random_negative_398 +CCTGTAGTGTTTTTCTTCGTAAATTATATCAAATGCAAATGCACAGCTTGAAATTTTAAGA +>random_negative_11340 +TTAAGAATGTGAGACTAGAGACGGGAAACCATCAAGAAAGTTGCCGTTGGACTAGTGACAT +>random_negative_8150 +ATGAAGACATAATGAAATTGTGGATTATGGGTTATTATATACGTGAGACAGAAGTATGGTT +>random_negative_20781 +ATCTGACTCATTCTTGTTAGTAGCTTCATAATAGTTATATGAATGCATTATAGGTCATTTC +>random_negative_5476 +TTATTTCTGGTATGTACACAGCAACCCTGCAGAGTAGGTTTCTATACCTCTATTTTAGCAG +>random_negative_12354 +AGATGATTTTTGTATTTTTTAGTAGAGACAGGACTTCATAATGTTGGCCAGGCTGGTCTCG +>random_negative_4642 +TGGGTTGAAAGCAGTGAGTCAATTGCCTACGCTCTGCTTTGTTCAGAATAAAATGCCTAAC +>random_negative_7686 +TCTCTTGTCACCCAGGCTGGAGTGAAGTGGTGTGATCTCGGCTCACTGCAACCTCTACCTC +>random_negative_16994 +CTGGCAGCCAAACCTCTCCTCCCCCTCACCTGACAGGTGCAGCGGCCTGGCTGGGGAGCCC +>random_negative_1617 +CTGGCGCTCCGGTAGGATCCAGGCTCACTTGGTATATCCCCTGCTGCAGATTACGGTCCAC +>random_negative_20337 +AGAGAGTCTGGTTGAAGCCCCAGGTCTGTGGTCGTTTGTTAGGGCTGCGGGAGCTGAGACT +>random_negative_14805 +TTGGATTGAGTCAGGTTCCACCCCAGTCCAGTCAGTTGTGGACTGAGAGGTGATGAGGCTG +>random_negative_11414 +CCCCTTCCCCACAGATGGTAGCGACCTCTGATTGGAGATCTACTGTGTAAGGCATCAGGAA +>random_negative_21800 +GACGGTGATCACTGTGGACACTAAGGCGGCAGGCAAAGGCAAAGTGACGTGCACCGTGTGC +>random_negative_22380 +CAGGTTCCTCTCGGGCACACACACAGCTCTGTGCCTGTGTGGGCACAGCCTTCCATGCCTC +>random_negative_933 +CAGGCGTGAGCCACGGTGCCCGGCCCCAGCCACCAGTTTTGTACAGCACTCAGGTGGGTGT +>random_negative_18591 +GAGGCTGAGGCAGGAGAATCTCTTGAACCCGGGAGGTGGAGGTTGCAGTGAGCCGAGATCG +>random_negative_17363 +AATGTAGTTCTCACCTTCTAAATATTACTTAAAATTGTTTTACAAAAATTTCAGCCTAGAA +>random_negative_8589 +CTTTAGGACCTCAGAGATGTAAGCATTTTAGCAGCCACACAAAATCTCTGGCTATGAAAGG +>random_negative_5064 +GTTGCTCAGTTCACCGAGATCTTAAAAACAATGTAACAGTTACAATACAGGCGTGTCACAG +>random_negative_15588 +TCAAAGTTTCTACTTAGAAATCAGAGTCCCTTAGAAATGATGTAAGCCTCTACTCCAGACT +>random_negative_13694 +GGCAGCTGCGGCAGACCTGGTCGGTGCCTGGGCCTTTTTCTCTGGTGTGGTTCTGTTGCTC +>random_negative_3303 +CCCGAGTAGCTGGGATTATAGGCATCCACCATCATGCCCAGCTAATTTTTGTATTTTTAGT +>random_negative_7611 +CGCCCGCCACCACACCTGGCTAATTTTTGTATTTTGATAGAGACGAGGTTTCATCATATTG +>random_negative_10144 +CCAAAAATACAAAAATTAGCCAGGTGTGGTGACCCATGCCTGTAATCCCAGCTACTCATTA +>random_negative_9329 +TTTTGCTCACATTTTTTAATTGGGTGTTTGTCTAAAGACAATTATCGATCATAGTAGGCTG +>random_negative_20922 +TAGCAGGTAAGCCCAGCTGCCAGAATTCGCTTCCAGAAGCTCATCCTTGTTCTTTGATGAT +>random_negative_20939 +TTAATAACGCATGTGCTGGTTTAGAACCCGGAGCTATAACAATTTAGGAGCAAGGAGAGAA +>random_negative_5492 +TAAGACATTAGTGGAGGCCAGGTGTGGTGGCTCACGCCTGTAATCCCAGCTCTTTGGGAGG +>random_negative_14512 +GTAATCTCAGCTACTCGGGAGGCTGAGGCAGGAGAATCGCTTGAACCCAGGAGGCGTAGGT +>random_negative_17635 +GACCCTGCTGCCTGCACTTGCCAATGTCTCTCTCTTTTTAATTTTGCGGAGAGGCTTCTGT +>random_negative_10854 +TGCGCTTCGTGCCGCTTATCTTGGCTCGCCTCCTTCTCATCTTTGATTATCTGCTTCATCA +>random_negative_15482 +GGTGGAGGTTGCAGGGAGTTGAGATTGCACCACTGCACTCCAGCCTGGGTGACAGAGCAAG +>random_negative_8201 +CTGTGCACTCATGCCCAGTGTCCCTCTTCTTATAAGGATACCAGTTCTACTGAATTAGGGC +>random_negative_1481 +TTGGGTCATGATGTTGAACTAAATGCCTCATGCTTCAGAGCAAGCTGATTAAATGAAATTC +>random_negative_21622 +TGTCTGTTGGGTGCTTTCTGGGAAACCCTTTACTGATAGGCCATGGCTGGGCCAGTCTTGA +>random_negative_17498 +CTGAGAAATACATTGTTAGGTGATTTCATTGTTGTACAAACATCACATAGTGCACTTACAT +>random_negative_18382 +CTGACTGTGAACCAGAGCCCAGGGACCAGGCGTCAGCCCCGTGCTGGCCGAAGGGAGAGGG +>random_negative_3638 +CCTGCCTTCCTGTGTCCTCTCTCTCCCTTCCCCTCCTGCTCTTGGAACCAAGGGCTCCTCG +>random_negative_7959 +GACTTGGGCACCAGGCAGCAGAGGGCAGGTGATCTTAGGGTGCCCCCTGGAGGGCAGGGCT +>random_negative_11539 +TGCATTTTGACTGACCTGTCACATGGGTCAGGTGTGGAATTTTACACTTGTGGCACCATGT +>random_negative_6708 +CAATGGCATGATCACGGCTCACTGTAGCCTTGACTTCCCAGGTTCAAGCAATCCTCCTACC +>random_negative_16492 +AAACCCCCCGGGGTTTGTGGCGCCGTGTTCTGGCAGGAAACAGGCCGACCCAAAAGTTGAA +>random_negative_2880 +TTTCAAAGGGCATTGATTTTTTTCATAAAACTTTTTAAATTAAGATCTGTGGGCCTGGTGC +>random_negative_22609 +CTGCCAGAAAGGGGCTTGTAGGAAGACACAAGGCTGTACCCTATCTCTCCAGGGGGCAGGC +>random_negative_18254 +TTTATTTTAAGCATGATGGTAAGATGTCTTTGGGGTGTTTTATGGGGTGAAATGATATAAT +>random_negative_16597 +GCATAATTTACACATTTCTAAATGCTCCCTCGGGGGAAAACAGGAAGAAATTGGTTGTAGA +>random_negative_5413 +AAAAGTTACTCCTTTGAGGGAGTTTGGCTGCTTTTGAGTGGAGGTGACTTCAGGCTTATTC +>random_negative_4412 +GTGTCCAAGACAAGGCATAGGTTTTTTGTTTGTTTGTTTTGTGACAGAGTCTCGCTCTGTC +>random_negative_16412 +CTCGATCATCCCCTCTCAGGCCAGCCAGGGAGTCTCAGCTCCTGCCCAGGACCTGGCTGGA +>random_negative_18599 +AGGGCTCCACCTTTGACCTCACTGAACCTTAATTACTCCTTAGAGGTCACGTCTCTAAATA +>random_negative_15871 +AATGCCAAGCCCGCCCTGGTCCCAAGAAAAAACACACCACACACACAAACATTAAAAAAAA +>random_negative_2755 +TTTCACAGATTGTCTTTTTTCTGTTTACCATGCCGTTGCTTTTCGCTGTCATCTTTATCAT +>random_negative_1215 +ACGCAGCTCGTGACAGCAGGGAGTGGAACCCACCAGGCAGCCAAATGGGCCTCCAAGGAGA +>random_negative_18664 +TAGTTAGGGGTATGAGCTCCCTTAGTGTGTGGGCCTCTCCTGTTCATCTTTTCGTTTTAAG +>random_negative_8547 +AGTTGATGCAGCTGAGCTCTTTCCATCCTGTCCTGGGTTGCTGTGTGCATTGCATTCTCTC +>random_negative_5845 +CCTCTACCTCATGGGTTCCAGGGATTCTCCTGCCTTAGCCTCCCGAGTAGCTGGGATTACA +>random_negative_8769 +TATAGATTTGAAAATAAACTTAAAAGCCCAGGGTGAAAACGTGTCATTGCTCTCCGCAGGC +>random_negative_13660 +CCAGCTCCATCCCTTCAGGCACCCTGGCCAAGTATCAGCTTCTCTAAGACTTGGTTTCCTC +>random_negative_9916 +TCAGATTCTTTCAATGCTAGGTTTAGTATCGTTCCTTTTTCTCCCATTTGGTGAAGTGGTG +>random_negative_21042 +AATTTAAAATAAAAGTTGAGGCCAGGTAGGGTGGCTCATGCCTGTAATCACAGCACTTTGA +>random_negative_20689 +TGTAATGTGTAAAGGGGAGGGAGAATGTGAGGTGCTGGGAAGCACCGGGCCCTTCGGGGGA +>random_negative_22534 +ATGGGGTTTCACTATGTTGGTCAGGCGCATCTCCAACTCCTGACCTCAGGTGTGATCCACC +>random_negative_21620 +AAGGGCTTTTCAAGGTTGAATAGGAGTTTGCAATGAGGAAAAAAAGTCACATGATCTTTCT +>random_negative_9401 +TAGACTCCCTTTTCCTAGTTGCCCACTCCCACCCCAGTCTGGTGAATGTTAGCCTTTTGGG +>random_negative_19360 +AGCTTTGCTGAGAATAGACCACAGGAGAGCAAGAGTCGAAGGCAGAAGACAGGTCAGGAAG +>random_negative_19844 +TCTTTGGTGTTTTCAGATACAAGCCTTTGGGGCAGCATCCCCTCTTGAGTATTTTTTCTGG +>random_negative_1724 +GCCACTGCACTCCAGCCTGGGCGACAGAGCGAGACTCTGTCTCTAAATAAATAAATAAATA +>random_negative_19807 +ATATCTGCTGCCATATTTTTCCAGGGGCTAGTTTGACTCTTCTACTTTGGAGGGCTTTGCA +>random_negative_11214 +ATATGTATGTTGTTAGATTGTTTTTTGTTGTTGTTTTTTGAGACAGAGTCCGGCTCTGTTA +>random_negative_23177 +TATAGTAATTTTTTATTGATGTGTGGGAAATTATTCCAAAATTTAGCAACTAGAAGCAACA +>random_negative_9875 +AAAGCTAAAGCAAAAACACTGGCATATGACCATGCAAGACTGTCAGTGCCAACAAAGACAA +>random_negative_14367 +TCTACCCACTAAGCACTCATAGCTCTCCTTCCCTAGCTGACAATAAAAAATGTCCCCAGAC +>random_negative_4027 +ACAAAGACGTTTCTCAGTGTTGAATACACTCTTCCTTAAAAACCTAAGGCTAGCCTCTGTT +>random_negative_22646 +TCCACAACACCCTGCCTATATGTTACCGGCCATTTTGTGTGTCCTTCTGATAGGATGCTAG +>random_negative_1645 +TTCTGACTGCCAGGTGTTCTTCACTCTATCCATTCTCTTTTGCCAGTAGATATATAAAAAG +>random_negative_20207 +GCCTCCTGGGTTCAAGCGATTCTCCTGCTTCAGTCCCCTGAGTAGCTGGGATCACAGGCAT +>random_negative_8009 +AGCTACATGATTTAACCAGAAACACCAGAAACTGTCCTGGTGGAAAATTGTTCTTTATCCA +>random_negative_18195 +CCGTGAAGCAGTGCACCGACCAGTTTGGGATGGACACAGTACTGGTGGAAGACAGGATGCC +>random_negative_8527 +CTGTAATGGGAACCCCTCCCCCATTTACTTCTCCACCTCCCGTCCTCCCCATCATTGGTTT +>random_negative_15810 +AAAAAAAAAAAGAAAAAAAATTGGCAGGGTGCGGTGGCTCACACCTATAATCTCAGCACTT +>random_negative_10743 +GTAGAAAAACGTAGTGGTTGTGTATTAACAGAAAATGCTTCTGAGAAGTTTATATCTAGTA +>random_negative_21468 +TTCTAAGGACAGCTGGTGTCCTCTGTAAGCAAACCAGGCTTGGCTAGGCCTGGGCCCTCTG +>random_negative_4787 +GCCAGTGGCTCCCCTGCCTCCTGCCGATTCGGCCTCCCTGATCTGACTGCATCCTAATGTA +>random_negative_16607 +GGTGTCCATTTGTGCAATGACAATGTTCATCTCACCTCCTGAGGCTGCTGGGGTTCAAGAC +>random_negative_407 +GGTAGGGGGATAGAGTCTCACTGCGCCACCCAGGCTGGAATGCAGTGGTGCGATCTCAGCT +>random_negative_19757 +GGGACTATAGGCGCATGCCACCACGCCCGGCTAATTTTTGTATTTTTAGTAGAGACAGGGG +>random_negative_13405 +GCTTGAACCCGGGAGGCAGAGGATGTTGCAGTAGCTGAGATCGCACCACTGCACTCCAGCC +>random_negative_14806 +GATGTGTGTCCATACTTCCATTCTCTTCCCCTGAACTCTTCTCCAGGTCCTGGAATCGCCT
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_out.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,2 @@ +chr1 1005 1008 s1,1006 6.500000 + +chr2 1994 1997 s2,1997 4.000000 -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_positives.parop.fa Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,50 @@ +>SERBP1_K562_rep01_125 +GCGAGGCCTGACATCACTTACCAGGAGCCTCAGGGAACCCAGCCAGCACAGCAGCAGCAGC +>SERBP1_K562_rep01_2383 +CTCTACGCGGTCTGGGCTGAAGCTGGTTTCCTGGCCGAGGCGGAGCTGCTGAACCTGAGGA +>SERBP1_K562_rep01_473 +TCAAGTACACGGAGAAGCTGCAGGAGCCCCCGGCCAGTGCTGTCCGTGAGGCTGCCGACAA +>SERBP1_K562_rep01_1962 +CCAGACGGGAAAACCATCTATGAGAACTCCTCTCCGTGAACTTACCCTGCAGCCCGGTGCC +>SERBP1_K562_rep01_58 +AGGCACAGGGCTGGAGCGAGGTGTGGCCGGCGTGCCAGCCGAGTTCAGCATCTGGACCCGG +>SERBP1_K562_rep01_1844 +CTTGTCCTGGCTGGACGCTACTCCGGACGCAAAGCTGTCATCGTGAAGAACATTGATGATG +>SERBP1_K562_rep01_1556 +CAAAATGACTATGAAGTTGGGCAGCGGCACGGGCTGGAGGCCATCAGCATCATGGACTCCC +>SERBP1_K562_rep01_3134 +CAGACAATGCCTGTGGAAGACAAGTCAGACCCCCCAGAGGGGTCTGAGGAAGCCGCAGAGC +>SERBP1_K562_rep02_1008 +TGCCTGCTGGTCACCCTGGCCGCGCGCTTCCCCGCCGACTTCACGGCCGAGGCCCACGCCG +>SERBP1_K562_rep01_571 +TGGAGAAGCCGGGGGTGGACGAGGAGCCGCAGCATGTCCTCCTGCGGTACGAGGACGCCTA +>SERBP1_K562_rep01_283 +CTGTCCTCGCCGTCACCGGGCCAGCAGGTGCAGACCCCGCAGTCGATGCCCCCTCCCCCCC +>SERBP1_K562_rep01_3147 +GCCTTTTACTTCGGCCCGCTTCTTCTGGTCACTCCGCCACCGTAGAATCGCCTACCATTTG +>SERBP1_K562_rep01_264 +TGATGAAGATGACCCTACTGCTGATGATACCAGTGCTGCTGTAACTGAAGAAATGCCACCC +>SERBP1_K562_rep01_1186 +GTTGCCAGCCAGGCTCCCCACACCATCACCTGGTATAAGCGTGGAGGCAGCTTACCCAGCC +>SERBP1_K562_rep02_155 +GTGTGATCAACGGCTCCCCCTGCCAGCACGGAGGCACCTGCGTGGATGATGAGGGCCGGGC +>SERBP1_K562_rep01_521 +GTGAGGATAATGCCCCAGCCACCAGCTACTGTGTGGAGTGCTCGGAGCCTCTGTGTGAGAC +>SERBP1_K562_rep01_941 +TAGACACGCAGCCCAAGAAGGTCCGGAAGGTCCCGCCGGGTCTTCCATCCTCGGTGTACCC +>SERBP1_K562_rep02_898 +GGAGGCTCTTCAGGAAAGCCTTCCCCCTGCTTTGCATGGCTCCCGGGGCGCTGACTGCGTG +>SERBP1_K562_rep01_3279 +GGCGAAGACGAGAAGAAGAGGAGCGTTGGAGAATGGAAATGAGACGTTATGAAGAGGACAT +>SERBP1_K562_rep01_237 +GCAGAGCTCCAGAGGATGGAACAAGAGGCTGAGAGGCGCAGGCAGCCACAAATAAAGCAAG +>SERBP1_K562_rep02_1199 +AACATTGGGAGCCTCATCTGCAATGTAGGGGCCGGTGGACCTGCTCCAGCAGCTGGTGCTG +>SERBP1_K562_rep01_309 +AGCTTCCTGCCCAGCCCCTCACCGCAGCCCTCCCAGAGCCCAGTGACGGCGCGGACCCCAC +>SERBP1_K562_rep01_2709 +AAAAAGGTGGAAGAGGTGCTGCAGCTGGTGGACGAGGTGGTACGAGGGGTCGTGGCCGAGG +>SERBP1_K562_rep01_2694 +TATCAGACATGAAATGACTCCAGTAAACCCTGGTGTTGGCCAGTGCTGCACTTCTTCATAT +>SERBP1_K562_rep01_2013 +CTGATGGGCCACAGGGACCTCCCGGCCTGCCGGGACTTAAGGGGGATCCTGGCGTGCCTGG
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_positives.train.fa Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,1000 @@ +>SERBP1_K562_rep01_1163 +ACACCCCAGCAGTCAAACCGTACAAGAAAAAGTCGTGTTTCTGTGTCTCCAGGGAGAACTT +>SERBP1_K562_rep01_290 +GGTGGGATTTCCTCCGCCGCCGCCGCCGCCGCCGCCGCGGGTCCTGCGCCGCGTCCAGCCC +>SERBP1_K562_rep02_1341 +AATATGAGCAGCTGTCCTCTGAAGCCCTGGAGGCTGCCCGAATTTGTGCCAATAAGTACAT +>SERBP1_K562_rep01_1961 +CAAAGGAGTGTGCAGACTTGTGGCCCCGGATTGCATCCAATGCTGGCAGCATTGCATGATT +>SERBP1_K562_rep02_453 +CTTCGGTCGCTACCGCTCCCGCTCTGCCACCCCCGCCAACCGCCGCTCGGGCCTCCGTCGC +>SERBP1_K562_rep02_29 +ACCGATGCCCAGATTGCACGACCACTTCTGGAGCTGCTCCTGTGCGCACAGCGCGAGGCGC +>SERBP1_K562_rep01_210 +CAACAGCAGCAGATGGCCGAGCTGCACAGCAAGTTACAGTCCTCCGAGGCGGAGGTGCGCA +>SERBP1_K562_rep01_2868 +CAGGTTTGCCAGCTGAGGAGCCAAAGGAGAAGTCCTCTCGGAAGGTAGCCGAGCCAGAGCT +>SERBP1_K562_rep02_1223 +GCTGGCAAAGGCAAAATGAGAAACCGTCGCCGTATCCAGCGCAGGGGCCCGTGCATCATCT +>SERBP1_K562_rep02_991 +GGATTGCCAGGGAATCAGGGCCCTCCAGGACCCAAGGGCGCCAAAGGAGAAGTGGGCCCCC +>SERBP1_K562_rep02_107 +AGAAAATGGGTCCTGTCGGGAATCCTGGCTAGCGAGGAGACTTACCTGAGCCACCTGGAGG +>SERBP1_K562_rep01_2186 +GAAGAAAGATAGAGGACGCAGGTCAGAGAGCAGCTCTCCTCGACGGGAGAGAAAGAAAAGC +>SERBP1_K562_rep01_27 +GGGCAGCGGGGGTCGGGGGACTGGCCAGCTCAACCGCTTCGTGCAACTCTCCGGGCGGCCG +>SERBP1_K562_rep01_2014 +TGAGCTGAAGGTGCGCAGGGACCCCCAGGTGAGCCCCATGCACTGCCTGGACGAGGAAGGC +>SERBP1_K562_rep01_955 +GCGGCGCGGATTGAATGAGCCCGCCGAGCCCGGGCCGCCGTCGGGAGCAGCGCAGGCCGCG +>SERBP1_K562_rep02_1397 +TTTGCATTGTTCCTCATCCGCCTCCTTGCTCGCCGCAGCCGCCTCCGCCGCGCGCCTCCTC +>SERBP1_K562_rep02_1446 +CGATTGGCATCCTCAGCCGCTTTTCTGCCTTCAGGATCCTCCGCTCCCGAGGTTATATATG +>SERBP1_K562_rep01_1271 +CAACCTGGTGCTCTGAACCAGCGCCAGGTCCAGTTCTCTGAGGAGCACTGGGTCCATGAGT +>SERBP1_K562_rep01_1542 +CGCTCCTATGCCTGGAAACTCCTGCCCGCCTGAAGTGGATGCAAAGCTGCTGAAGCGGCAG +>SERBP1_K562_rep01_173 +GGCTCTTCGACTACCGGGGCCGTCTGTCGCCCGTGCCAGTGCCCAGGGCGGTCCCTGTGAA +>SERBP1_K562_rep01_2934 +CAGTCCCTCCTGTAGCCGCCGCCGCCGCCGCCCGCCGCCCCTCTGCCAGCAGCTCCGGCGC +>SERBP1_K562_rep02_224 +CCCTCGGGGGTCGCGGCCGCCCTCCGCGGCCCCTCGTGGTGCGCGCCGTCCGCTCGCGCTC +>SERBP1_K562_rep01_1161 +CCGCAACGCTCGACCCCAGGATTCCCCCGGCTCGCCTGCCCGCCATGGCCGACAAGGAAGC +>SERBP1_K562_rep01_1370 +ACAAAAGTGCATTTTTATGTGGAGTTATGAAGACCTACAGGCAGAGAGAGAAACAGGGGAG +>SERBP1_K562_rep01_1830 +CGGTTTACCAGCAGCCCCAGCAGCAGCCGGTGGCCCAGTCCTATGGTGGCTACAAGGAGCC +>SERBP1_K562_rep02_1530 +ATGAGCCGTCCTGGGGAGGTGTGCTCTGCTCTCAACCTCTGCGAGTCTCTCCAGAAGCACC +>SERBP1_K562_rep01_761 +CAAAGGTCGTGGATCCAAGCACCTCCTGGAGTGCGAGCGCTGCCGCCATGCATACCACCCG +>SERBP1_K562_rep02_1207 +CGCCATCGCCGTCATGCTGGGCGCCGCTCTCCGCCGCTGCGCTGTGGCCGCAACCACCCGG +>SERBP1_K562_rep01_1911 +CCTGATTGATGCCGTCACGGGGCTCAGTGGCAGCGGCCCCGCCTACGCATTCACAGCCCTG +>SERBP1_K562_rep01_1333 +CACGGTGATCATGTCTCGGATGATTCTGGGGGAGTACACAGGGCTGCTGGTCAACCTCTCC +>SERBP1_K562_rep02_215 +CTTCAGGTTACTTCATGGCAGCTATCCCACAGACTCAGAACCGTGCTGCATACTATCCTCC +>SERBP1_K562_rep01_3203 +GGCGGCCGCCGCGCTGTGGCTGCTGCTGCTGCTGCTGCCCCGGACCCGGGCGGACGAGCAC +>SERBP1_K562_rep01_2285 +CATGGACATGGTGGAGAAGACGCGGCGCTCGCTCACGGTGCTGCGCAGGTGCCAGGAGGCC +>SERBP1_K562_rep01_1761 +TGGAACGCCCCTTTGTCCTGGCCAGGGCCTTCTTCGCTGGCTCCCAGCGCTTTGGAGCCGT +>SERBP1_K562_rep01_3110 +AGCCAGGCTGGAGAAAAGAAGCTGCCACCATGGTTGCACTTTCACTGAAGATCAGCATTGG +>SERBP1_K562_rep01_893 +AGAGGGGCCTGTCTGGGCCCTCGGGGCCGGGGCACATGGCAAGCCGCGGTGGAGTGGCGGG +>SERBP1_K562_rep01_1917 +ACCGGTGGGAGCTAGGCGCGAGGCTCGGAGTGCGGCCAGCGGGCGGAGGCGGTCTCGCATC +>SERBP1_K562_rep02_626 +GTGTACCTGCTGGTGGGGCTGTAGCCGTCTCTGCTGCCCCAGGCTCTGCAGCCCCTGCTGC +>SERBP1_K562_rep02_1471 +GAAGGACGGCAGGCCAAAGTGGAACAGTTGGGACCCTAGGAGGCAGCGGCAGTTGTCAATG +>SERBP1_K562_rep01_213 +TCCAGCAGAAGGAGATCACACAGAGCCCATCCACGTCCACCATCACCCTGGTGACCAGCAC +>SERBP1_K562_rep01_2393 +AGCCCAAGCGAAGACTGTCGGCCGCCAGAAGAGCCGGCACCTGTTGTGCAAATTGTCAGAC +>SERBP1_K562_rep01_2222 +GCACGTGTCCCTGCCTGGCACGCGCCTCCCGCGCTGGGCTCACAGGCAGGATGCAGTGAGT +>SERBP1_K562_rep02_768 +TTCCTGCCGTCGCGTTTGCACCTCGCTGCTCCAGCCTCTGGGGCGCATTCCAACCTTCCAG +>SERBP1_K562_rep02_1277 +GCTGCCACAGTTGGGGTGGCTGGTTCTGGGGCTGGGATTGGAACTGTGTTTGGGAGCCTCA +>SERBP1_K562_rep01_3186 +CTGACCTCGCTGGTGATCGAGAACGAGGCTGGGGATGAGCGCATGCTGGCGGATGCCCCAC +>SERBP1_K562_rep01_476 +TTTTGTGCCGAAGCTAGACCAAGTGGTGGAATCTCCAGCCATCCCCAGGATTCCCTGTGCC +>SERBP1_K562_rep01_376 +CGGAGAGACGGACCCCCTGATCCGGAAGTGCATGCTGCTGCCCTGGGCCCCCACCGACATG +>SERBP1_K562_rep02_485 +AAAATAGCTCCGAGATACAGTGCACCTGTAATCCATGTCCTGGACGCGTCCAAGAGTGTGG +>SERBP1_K562_rep01_1936 +CCGGCGTTCAAGATGTCGAAGCGAGGACGTGGTGGGTCCTCTG +>SERBP1_K562_rep02_376 +GAGCAGGAGCGTTGCATCACCATCAAGTCAACTGCCATCTCCCTCTTCTACGAGCTCTCGG +>SERBP1_K562_rep01_2588 +AAGATTGGGAATGGATGGCTACAGGGGAATCAGCCTAGCAAACTGGATGTGTTTGGCCAAA +>SERBP1_K562_rep01_846 +CGTCATCATCTCCACCTACGGCGAGGGCGAGAGCGGCCCCATGGGCAACATCATGATCGAT +>SERBP1_K562_rep02_1527 +AAGACCTGTGACTGGCTTCCGAAACCGAACATGTCTGCTTCATGCAAGGAGATAGTGGACT +>SERBP1_K562_rep02_808 +CAAGCGCTTCTCGGGCACCGTCAGGCTTAAGTCCACTCCCCGCCCTAAGTTCTCTGTGTGT +>SERBP1_K562_rep01_768 +GGCTGTGGGAGGTGTTGGCGGCGGCGGCGCGGGCGCCTGAGGAGGAGGAGGAGAAGCGGAT +>SERBP1_K562_rep02_637 +GAGGGGAAGCTTGGGATCATGGAATTGGCCGTTGGGCTTACCTCCTGCTTCGTGACCTTCC +>SERBP1_K562_rep01_793 +CGCATGCGGAGGCTCATGGCTGAAGATGAGGAGGGGTACCGCAAGCTCATCGACCAGAAGA +>SERBP1_K562_rep02_1098 +GCTGGGCGCGGAGGAGCCACTCAGCAGCATGACAGACGACATGGGCAGCCCCCTGAGCACC +>SERBP1_K562_rep02_514 +TGCAGCTGAGATCCTGGCGCGAGATGGTCCCAACGCCCTCACTCCCCCTCCCACTACTCCT +>SERBP1_K562_rep01_2180 +CGAGAGCGATGAGGAGGAGGTCAGGGCCCACCTCCGTTGCGTGGCCGAGCAGCCGCCCCTC +>SERBP1_K562_rep01_645 +GGGGAGCCCTGGAGGGCGGGCTTCCAGTGGGGGGAGAGCCCCTGGCAGGTGATGGCTTCTC +>SERBP1_K562_rep01_63 +GAAAAGGGCTAAGATTCGGCCATGAGCAGCGCCCCTCGGCGCCCCGCCAAGGGCGCAGATT +>SERBP1_K562_rep01_2264 +GGAAGAAGAGGACCGAGAAGTAGCAGCTGCTGTCCGGGCCTCCGTGGCCGCACAGCAGCAG +>SERBP1_K562_rep01_245 +GCGGCGACGACCTGGACCCCAACTACGTGCTGAGCTCGCGGGTGCGCACGGGCCGCAGCAT +>SERBP1_K562_rep02_592 +GTGGGGCTGTGCACTGGGCAGATCAAGACTGGTGCCCCTTGCCGATCTGAGCGCTTGGCCA +>SERBP1_K562_rep01_1352 +AAAGAGAGGAAAGTTACAGCCGAATGGGCTACATGGATCCACGGGAAAGAGACATGCGAAT +>SERBP1_K562_rep02_832 +CCCCTCGAGTGAGACTGGGACAAGATGCTCTGCTGGACTTGAGCTTTGCCTACATGCCCCC +>SERBP1_K562_rep01_2823 +CCTTTCAAGGTCCCTGTGCATGATGTGACAGATGCGTCCAAGGTCAAGTGCTCTGGGCCCG +>SERBP1_K562_rep02_297 +CTGTGGGCTCTTATCACTGTACCTGCGAGCCCCCACTGGTGCTGGATGGCTCGCAGCGCCG +>SERBP1_K562_rep01_2287 +TGAAAAGACAGATGGAGCGTATCCGTGCCAAGCAGGAGAAGCACAGGCAGGGCCGGGTGGA +>SERBP1_K562_rep02_1393 +CATCACCGCTTCTGGAAGTGGAGCCGCCACCAAAATGCAGATTTTCGTGAAAACCCTTACG +>SERBP1_K562_rep01_2466 +GAGCTGGATGGTGAAGGTCGGCACTCTTCACCCTCCCGAGCCCTGCCCGTCTCGGCCCCAT +>SERBP1_K562_rep01_3059 +GAATGACTCGGACCTCTTCGGGCTGGGGCTGGAGGAGGCCGGACCCAAGGAGAGCAGTGAG +>SERBP1_K562_rep01_2629 +CCAAACTGAGGAGCCCGGAGCTGCCGCTGGGGGATCGGGGCCGGGGGCACCCGGGGGAGCC +>SERBP1_K562_rep02_944 +AAACTGAGCAACTTCAAAACAGCAGCCGAGAGCTTCAAGGGCAAGATCCTGTTCATCTTCA +>SERBP1_K562_rep02_717 +AGACACCAATCTGGATTGAGCGGGTGGTGATAATAGGGGCTGGAAAGCCAGCAGCTGTGGT +>SERBP1_K562_rep01_3187 +CTCTATGATTGATTACCTCATCTGGCCCTGGTTTGAACGGCTGGAAGCAATGAAGTTAAAT +>SERBP1_K562_rep01_481 +GCCAGAGCCGAGGAGAACCCCCGCTCCCTGAGGAGGACCTGTCCAAACTCTTCAAACCACC +>SERBP1_K562_rep01_1802 +TCTTGCCCATCCTGCAGCACATTTCCCGCAACAAGGAGCAGGGCACCTATGAGGACTTCGT +>SERBP1_K562_rep02_940 +GGGGGTGTGAAGATGGGACTTCCAAGGCGCCTGGCAGTCCGCCTCGGGGCCCAGGCCCTCC +>SERBP1_K562_rep01_600 +CTCCGAACCTTCTCCCTGTCTCCGGATGCCCCGCGCCTCGCTGCTCCCCGGCTCTTGGAAG +>SERBP1_K562_rep02_556 +TGGAGGCGTCTGAGGGGCGGACGGAGGCGGCGGCGGCGGCGGCGGGAGCGGGAGCGGGCGG +>SERBP1_K562_rep01_721 +GAGGGAAGCGGGCAGCAGGGCGGCGGCGGGAGCACGTCCTCAAGCAGCTGGAGCGGGTCAA +>SERBP1_K562_rep01_214 +GAGCTGAAGAAGTTACCGCCCCTGCCTGCAGTTGAACGAGTAAAGCCTAGAATCAAAAAGA +>SERBP1_K562_rep02_1024 +CTGGTGACCCTGGCCGCCCACCTCCCCGCCGAGTTCACCCCTGCGGTGCACGCCTCCCTGG +>SERBP1_K562_rep01_2940 +GGAGCACTGGACATTCTGCAGATGCTGGGACGTGCCGGAAGACCCCAGTATGACACCAAGG +>SERBP1_K562_rep01_2781 +GTCACGTTTGCCGGCGTGCCCATCCCTCGCAGCCCCTACACTGTCACTGTTGGCCAAGCCT +>SERBP1_K562_rep02_1558 +GAGAGGGAGCCGGTGTCCTACGTCAGAGCCGCCGCCGCCGCGGAGCCGCCGCCGGGGAGGA +>SERBP1_K562_rep01_470 +GCTTCCAGAAAGCGCTCAGCTGTGCCCAGCAGGCCCAGCGTCCCCAGCTGCAGAGGCAGGT +>SERBP1_K562_rep02_67 +CGAGAGGCGGCTGGACGCCCTGGAGCTCCGCGGCGTGGAGCTGGAGAAGCGACTGCGGGCG +>SERBP1_K562_rep01_1896 +GGATGGTTTTAAGAAATTCCTGGAGAGCGGTGGCCAGGATGGGGCAGGGGATGATGACGAT +>SERBP1_K562_rep02_57 +ACCATCACTGAGAGCAGCAGCCTCCTCCTGTCGCAGCTCACCAGCCTGGACCCCCAGGGGC +>SERBP1_K562_rep02_211 +CCGTCCCGCTCCTAAGGCAGGAAGATGGTGGCCGCAAAGAAGACGAAAAAGTCGCTGGAGT +>SERBP1_K562_rep02_277 +CGAGATGATCGGCCACTACCTGGGCGAGTTCTCCATCACCTACAAGCCCGTAAAGCATGGC +>SERBP1_K562_rep01_1259 +GTGAGCTGCGCCGACCGCTCTGAGGGTTCGTGGCCCACCGCTCCTTCGCGGTCCCTGCCGC +>SERBP1_K562_rep01_948 +CGGCCCCGGCCGCCGCCGCCGCGATGGGCAACGCCGCCGCCGCCAAGAAGGGCAGCGAGCA +>SERBP1_K562_rep01_89 +GGACGGCAAAGCTCTGGGCGCCCTGGTGGACAACTGCGCCCCCGGTCTCTGCCCCGACTGG +>SERBP1_K562_rep01_956 +CCCGCAGGAGAAGAAGCGCAGGAAAGACAGCAGCGAGGAGTCGGACAGCTCAGAGGAGAGC +>SERBP1_K562_rep01_291 +AGACGCAGATGGCTCGTTCGGAACACCACCTGGATACGGCTGCGCTGCAGACCGGGCAGAG +>SERBP1_K562_rep01_2865 +GTGAGGAAGAGGATGGAGATGAAGATGAGGAAGCTGAGTCAGCTACGGGCAAGCGGGCAGC +>SERBP1_K562_rep01_85 +GAAAGCCATCGCCTATGGGCCTGGCATCGAGCCACAGGGCAACACCGTGCTGCAGCCTGCC +>SERBP1_K562_rep02_1063 +GAGCGGGGCAAGCCCTCGGAGCAGCTGACCCCAACCCGAGCAGAGAAGCTGAAGGATGCCG +>SERBP1_K562_rep01_1108 +AGCAATGGCAGTGACGGCGTTGGCGGCGCGGACGTGGCTTGGCGTGTGGGGCGTGAGGACC +>SERBP1_K562_rep02_631 +CGTCTTCTGGCTGGCTGGAGGCGTGATCCTGGGTGTGGCCCTGTGGCTCCGCCATGACCCG +>SERBP1_K562_rep01_2593 +GCCGTCATGTCTAAGTCAGAGTCTCCTAAAGAGCCCGAACAGCTGAGGAAGCTCTTCATTG +>SERBP1_K562_rep01_3026 +TGTCCTCTATACCTGTGTCCGATGCTGGAGGCCCTCGAGGAAGGGGGGCCGCCGCTGACCC +>SERBP1_K562_rep01_2502 +GGGACTATCCTCTGGAGGCTGTGCGCATGCAGCACCTGATAGCTCGTGAGGCTGAGGCAGC +>SERBP1_K562_rep02_928 +GGACACTGTGCTACCACTGGCTGGGCCGCAGGGTGGGCGTCCTGCAGGGCCAGTGCTGGGA +>SERBP1_K562_rep01_2380 +CTCATCCTGGTGGAGGACGTGAGGGTGAGCCCAGAAGAGGTGACCATCTACAACCACCCTG +>SERBP1_K562_rep01_3232 +TCTAACTGTAGCCCTTCCTGTGTTCCTGGTTATCCTCTTCTGCTGTTCTGGAAAGAAACAG +>SERBP1_K562_rep01_899 +CAGCAGGCCCCGGCTCCTGTGCCCCAGCAGCCGCCCCCGCCTCCCCAGCAGCCCCCACCGC +>SERBP1_K562_rep01_3142 +CCGGCCCGGCCCCAGCCCGCGCCTCTCCGCGCCGCCCCGCGCTCCGCACCGCGCCCTCTCC +>SERBP1_K562_rep01_2421 +CAGCCCCTTTCTCTTCCGGTTCTAGGCGCTTCGGGAGCCGCGGCTTATGGTGCAGACATGG +>SERBP1_K562_rep01_3092 +TTGTCCCCGGAACCGCCCTGCTGCCGCCGCCTGCTTCCTCTGCTCGCGGTTAGCCCGTCAG +>SERBP1_K562_rep01_377 +TTTGCGTGTCGCAGCGGCACCATCCAGTGCATCCCCCTCCCCTGGCAGTGTGACGGCTGGG +>SERBP1_K562_rep01_954 +CCCCACGCTGGAAGGGATCATCCAGCAGCTCGTCAACGGCATCATCACGCCCGCCACCATC +>SERBP1_K562_rep02_789 +GAATCTTTGCCACCTCCTCATAGCTCTGGATTCTTGGGCTCTAAGCCTGAGGGCCCAGGCC +>SERBP1_K562_rep01_32 +AGAGCGATGGCTTTTTTCACCCAGAAGGCCAGCCCCAGCGGCTTCCCCAGCCTCCGGAAGT +>SERBP1_K562_rep01_2178 +AGATCCGGCTCAAATATTTTGATACTGTACCCGTTGCTGCTGCCATGTGTGTGCTTAAAAC +>SERBP1_K562_rep01_769 +GACCACGGTCACCGCCCAGATCCTGCTGAAGGCCCTCACCAACTTGCCGCACACAGACTTC +>SERBP1_K562_rep01_2441 +GCACAACGCCATTGGCTTCTCCCTTCTCCGCGCGCCGCCGCCGTCTCCCACCTCCGCCTCA +>SERBP1_K562_rep01_1528 +TACCACCAGTTGAAGAAGCTTGGCAGCTCCTTGGACTGGGATCGAGCCTGTTTCACCATGG +>SERBP1_K562_rep02_1550 +ATCTCCTCAGATGGCCAGTTTGCCCTCTCAGGCTCCTGGGATGGAACCCTGCGCCTCTGGG +>SERBP1_K562_rep01_1122 +AAAGGGAAGGACATGGTGGTGGACATCCAGCGGCGGCACCTCCGGGTGGGGCTCAAGGGGC +>SERBP1_K562_rep01_21 +CCCCCGGTGTGGACCCCACCCAAGTTTCCTCCTCCCTGTCCCCTGAGGGCACACTGACCGT +>SERBP1_K562_rep01_920 +CTCATCAAGAACCCAGCGGAGCGGGCGGACCTGAAGATGCTCACAAACCACACCTTCATCA +>SERBP1_K562_rep01_659 +AGGGGAAGAAGCACCAGACCAACCTGGCCCGGCGAGCAGCCAAGGAGGCCAAGGAGGCCCC +>SERBP1_K562_rep02_1113 +GGAGGCGGAGGCGGCGGCAGCTCCTGAGCGGGGAGGCGGGAGCTGCGTGCTGTGCTGCGGA +>SERBP1_K562_rep01_3040 +ACTGCTGCACAAGGGGCAACACCCTCCACTAAAGAGTCAAGCCAGCCGGACGCATTCTCAT +>SERBP1_K562_rep02_547 +AAGCGCCGGGCCCTGCTGCGGGGGGGAGAGCCACTGACGCCGGGACCGGGACCGCCGCCGC +>SERBP1_K562_rep01_1829 +AAAGATCTTTTGAGGTCGAGGAGGTCGAGACACCCAACTCCACCCCACCCCGGAGGGTCCA +>SERBP1_K562_rep02_1013 +AAGCTGGAGCCTCGGTGGCCATGCTTCTTGCCCCTTGGGCCTCCCCCCAGCCCCTCCTCCC +>SERBP1_K562_rep01_1248 +GGGCCCAGAGTCCAAGTGAGCCCAGAGAGGACCCAGGTCCACGCAGGCCGCACCGTCAGGC +>SERBP1_K562_rep02_142 +GAAATCCAAGCGTTGGAGGTCCTGAGGCCAGCCTAAGTCGCTTCAAAATGGAACGAAGGCG +>SERBP1_K562_rep01_1601 +CTGCCCGCCCGCCGCCATGCCGCCCTTACTGCCCCTGCGCCTGTGCCGGCTGTGGCCCCGC +>SERBP1_K562_rep01_2031 +TCATGTGTGAGAGGCTGGGTGAGACTCGGAGCCGTGGGTCCCGACTGAACATCATCATCAT +>SERBP1_K562_rep01_1358 +ATATGTAGAGATTCTCGGGGAACAGCGACATCTCACTCATGAAAATGTACAGCGCAAGCAA +>SERBP1_K562_rep01_2813 +GACCCAGGTGTACGAGAGGCTAGAGAAGCTGCAGGCAGTGGTGGCGGGGGTGCCCGGGCAT +>SERBP1_K562_rep02_766 +CGCCCACTTACCTCACCTCTGCGCCAGGCTGCGGATGAGGATGACAAGGGGATGAGGAGCG +>SERBP1_K562_rep02_365 +TACGGCGGCGGCAGTGAGGGCGGCCGGGCCCCTAAGCGGCTCAAGACTGACAACGCCGGCG +>SERBP1_K562_rep01_3276 +GCCTGGCCCTACCGCCCCCAGCCCTACCAGCCGCCCGCCCTGGGCTGTGGACCCTGCGTTT +>SERBP1_K562_rep01_90 +ATTGTCCGAGGTCAGCCTCGTGGTGGGCCTCCTCCTGAGCGGCAGATCAACCTCAGCAACA +>SERBP1_K562_rep01_1919 +GGAGGGTCAGGGCCATCTCTGCTGCCAACCTGCACCTAAGGACCAATCACATCTATGTTTC +>SERBP1_K562_rep01_1801 +CGTTCCTGCTGCTGCCGCCGCTGCCCGAATCGGAACCGTCGGGCCGCAGCCGCCGGCAATG +>SERBP1_K562_rep02_1362 +AAGAGGTACCCCGGAGCCCCTTCAAGGTCAAGGTGCTGCCTACTCATGATGCCAGCAAGGT +>SERBP1_K562_rep02_257 +TTGCCAAAACCCTGGCCCAGCTGAACCCCGAGTCCTCCCTGTTCATCATTGCCTCCAAGAC +>SERBP1_K562_rep01_480 +TGCCGAGGGCCACGTCACCATGTTCCTGCTGAAGAGTGACTCCTACGGTGGCCGCCACCAC +>SERBP1_K562_rep01_2001 +CCCCTCGCCTGCCCGAGCCCCAGCCCTACCCCGGAGCCCCGCACCACAGCTCCTACGTGCA +>SERBP1_K562_rep01_1421 +TGGAATCCACGAAGACTCCACTAACCGCCGCCGCCTGTCTGAGCTGCTGCGCTATCATACC +>SERBP1_K562_rep01_1339 +CTGAAAATGTCAACAATGGCAACCCCTCTCCCCTGGAGGCCCTGCTGGCAGGCGCAGAGGG +>SERBP1_K562_rep01_2118 +CCCAGGATGCTGGGGAGTCCTGCACCCCAGAGGCCGAGGGCCGCCCTGAGGAGCCATGTGG +>SERBP1_K562_rep01_3234 +TCGCAACAGGAGGGCGGATCGTCCCCAGGTTCTCAGAGCTCACAGCCGAGAAGCTGGGCTT +>SERBP1_K562_rep02_216 +AGGCTCCAACTCGTTATGAAAAGTGGGAAGTACGTCCTGGGGTACAAGCAGACTCTGAAGA +>SERBP1_K562_rep01_2936 +GCCTCCTATCTGCCCGCCGCTCGCGCCGGGCCCGTGGCCGGAGGACTACTGAGCCCAGCCA +>SERBP1_K562_rep02_1165 +AACGGCACCTTTAACCCCCGCGCCCTGGCTCAGGGGCCCTGGTGGGCACGGAAGCGGCTCA +>SERBP1_K562_rep01_67 +GACTCACACCACCAGAAGCCTGTTAATGCTATCATCGAGCATGTGCGGGACGGCAGTGTGG +>SERBP1_K562_rep01_1194 +GCCGCAGCCACCGGTGCCTTCCTTTCCCGCCGCCGCCCAGCCGCCGTCCGGCCTCCCTCGG +>SERBP1_K562_rep01_674 +GAGCCCTTGCCGGGGCTGACCCGGGAGCCTGTGGCTGAGAGCCCTAAGAAGAAGCGGTGGG +>SERBP1_K562_rep01_687 +TAAGGGCCCAGAGGGCAAGGTGGCCGGCCCCGCCGACGCCCCCATGGACTCTGGTGCTGAG +>SERBP1_K562_rep01_2797 +ACAAGTTCACTGTGGAGACCAGGGGAGCTGGCACGGGCGGCCTGGGCCTGGCTGTAGAGGG +>SERBP1_K562_rep01_880 +GGAGCTGCCTGCAGGAGGGGGCCTGCCCCCGGAGCTGCCGCCCCGGCGAGGGAAGCCACCA +>SERBP1_K562_rep01_2155 +TCCCGCAGTGCCCGGGCTGCCTCCGGGCCTCCCGCCGGCCGTCTCCTTTGGCTCCCTGCAG +>SERBP1_K562_rep01_2801 +TGGGACGCCAGCAAGCCCGTTACCAATGCGCGAGAGGCCATGCAGCAGGCGGATGACTGGC +>SERBP1_K562_rep01_2739 +TGCTACATTCCCCTACGTGGTCCTGGTCGTGCTGCTGGTGCGTGGAGTGCTGCTGCCTGGC +>SERBP1_K562_rep01_1780 +CATCCCTACATTTTACACCTATGAAGAAGGATTATCCCATCTAACAGCAGAAGGCCAAGCC +>SERBP1_K562_rep01_777 +GTTTACCTGCGCCTGCCCGGACGGCATGCTGCTGGCCAGGGACATGAGGAGCTGCCTCACA +>SERBP1_K562_rep01_1014 +CCTCTCGCCTGCGCCATGGCCGGCCGGTCCCACCCGGGCCCGCTGCGGCCGCTGCTGCCGC +>SERBP1_K562_rep01_1425 +GCTCGGCCGGTCGCCGTTTCCAAGATGGCCGCGGCGCGCACGGCTCCTGCGGCGGGG +>SERBP1_K562_rep01_1738 +TGTGGGGCGGATGTGGGTGGCTTCTTCAAAAACCCAGAGCCAGAGCTGCTTGTGCGCTGGT +>SERBP1_K562_rep01_662 +GCCCATGAAACGCCCAATGGAGGAGGACGGGGAGGAGAAGTCGCCCAGCAAAAAGAAGAAG +>SERBP1_K562_rep02_64 +TCAGCGCCTACCTGATCTACTTGTCCCAGCACACGCCTGTGGAGGAGCAGGCCCAGCACAG +>SERBP1_K562_rep01_2918 +CGCTGCCATGAAGGGGGTCAGTCCTACAAGATTGGTGACACCTGGAGGAGACCACATGAGA +>SERBP1_K562_rep02_853 +GGTTTTAGACAATTACTTAACATCCCCCCTCCCAGAAGAAGTGGATGAAACCAGTGCTGAA +>SERBP1_K562_rep01_2477 +AAACACCTGGAAATGGAGATGGTGGCAGTACCAGTGAGACCCCTCAGCCTCCTCGGAAGAA +>SERBP1_K562_rep02_13 +CAGCTGACCGCCAGCATCCGTGCCCCCTCGGGCAACGAGGAGCCCTGCCTGCTGAAGCGCC +>SERBP1_K562_rep01_2687 +GCCTGGCGGGCAATTCTATTGGGTTTTCTCATCACTCTGCGTGGCTGGTGGTGCTGCCAGC +>SERBP1_K562_rep02_1289 +CGGGCGGTTGGCGTTGCGCAGAAGGCGGCGGCGGTGGTGGCTTGTGGTGCGGCCTCACCAT +>SERBP1_K562_rep01_1119 +CTCTACCGAAAAATGGAAATCTATCGCCCTCACAAAGCCAATGCTGAGGAGATGACCAAGT +>SERBP1_K562_rep01_2259 +TGATGGCTTCAATGTCTGCATCTTTGCGTACGGCCAGACGGGCGCCGGCAAGACGTACACG +>SERBP1_K562_rep01_747 +AATGGAGGAAGAGAGCGGCGCGCCCGGCGTGCCGAGCGGCAACGGGGCTCCGGGCCCTAAG +>SERBP1_K562_rep01_2022 +GCATCAGCGAGGAGGTGGGGCTGCTGCAGCTCCTTGGGGACCCCCCGCCCCAGCAGGTCAC +>SERBP1_K562_rep01_620 +AGAGCCAACGGGCTGAAGTCTTGTGTCATTGTGATCCGGGTCTTGAGGGACCTGTGCACTC +>SERBP1_K562_rep01_2191 +GCAAACGTAAATCTAAGGACAAAAAGCGAAAGCGGTCTCGAAGTACAACACCAGCCCCCAA +>SERBP1_K562_rep01_551 +TGGAGTCAGAGCGAGAAGCCCGGAGGTTGCGCTGAGCTTGGCTGCTCGCTGGGTCTTGGAT +>SERBP1_K562_rep01_1913 +CAGTTGTTACTCAGGTGCGCTAGCCTGCGGAGCCCGTCCGTGCTGTTCTGCGGCAAGGCCT +>SERBP1_K562_rep01_2818 +GAGACGCAAGTCAAAGAGATGCGCTGGCAGCTGAGCGAGCAGCTGCGCTGCCTGGAGCTGC +>SERBP1_K562_rep02_1271 +GCGCCATCTGCTCGCGGCGCCGCCTCCTGCTCCTCCCGCTGCTGCTGCCGCTGCCGCCCTG +>SERBP1_K562_rep02_696 +CGGGAGCTGTGCCAGGGCCTGGGCCAGCCTGGCTCTGTGCTGCGGGTGCTCTGGTTGGCCG +>SERBP1_K562_rep01_2213 +GCCGCCCCGGAGCGCCCCGGAGCCCCCCGCCGTCCCGCCCGCGGCGTCCCGCGCCCCGCCG +>SERBP1_K562_rep01_122 +GGCTGAGTGCAGACATGGCCACTGTCCTGCAGCTGCTACAGAGGCAGATGACGCTGGTCCC +>SERBP1_K562_rep01_1879 +CTGAGCACGCGGTGGTGCTGGAGATCGCGCCCCACGCCCTGCTGCAGGCTGTCCTGAAGCG +>SERBP1_K562_rep02_1148 +GAAGATTGAAGCCAGAGAAAGGAAAGCCAAGATGACAGATTTTGATCGTTTTAAAGTTATG +>SERBP1_K562_rep02_657 +CCCAGGATGCTACCACCAACCCGTCCCTGATCCTGGCCGCAGCACAGATGCCCGCTTACCA +>SERBP1_K562_rep01_1243 +TACCGGGCCTGCTTGTATGCTGGAGTCAAGATTGCGGGGACTAATGCCGAGGTCATGCCTG +>SERBP1_K562_rep01_2582 +GTGCCGATGTCTTTGCCAGGTACTCTCGCCTCCGCCAGTGGAACACCCTCTATCTGTGTGG +>SERBP1_K562_rep01_68 +CGTCACTGAAGAAATCATTCCCCTCGGGAATCAGGAGTGACCTGGAGCACTGTGGGGACGG +>SERBP1_K562_rep02_476 +ACACCAAGATTGGCCCCCGCCGCATCCACACAGTCCGTGTGCGGGGAGGTAACAAGAAATA +>SERBP1_K562_rep01_62 +CGGAGACCTTAAGGGAACAGCTCTCATCGGCCAATCACTCCCTCCAGCTGGCCTCACAGAT +>SERBP1_K562_rep01_42 +GGAATCATTTCCCCCTGCGCCTCTGGAGGAGGAGATCTTCCCTTCCCCGCCGCCTCCTCCG +>SERBP1_K562_rep02_1123 +TCTCCGGGCTGCGCCGCCGGAGCCGGGACGCGCCTCCGCAGCCCTCGCCGCCTCCATCCCC +>SERBP1_K562_rep01_443 +TGAATGGTGTGGCTCTGCAGGGCGCCGAGCACCACGAGGCCGTGGAGGCGCTCCGGGGGGC +>SERBP1_K562_rep01_949 +TGCACAGCTGGACTACCACCGGCAGGCCGTGCAGATCCTGGACGAGCTGGCGGAGAAGCTC +>SERBP1_K562_rep01_562 +GCCCCTCGCCTTCCTCTTTCCGTCTCAGGTCGCCGCTGCGAAGGGAGCCGCCGCCATGTCT +>SERBP1_K562_rep02_1459 +GGTCGGCTCCTGGCCGGAGCAAGATGGCTGAGGGCGAGCGGCAGCCGCCGCCAGATTCTTC +>SERBP1_K562_rep01_1522 +CGGTGCACTGCTGTTGCGCCAGGGACCGGGGGAACCGCCGCCCCGGCCGGACCTCGACCCT +>SERBP1_K562_rep02_15 +GAATCGCACAGGTGTGGAAGTCGGGAAGCCCACCCACTTCACGGTGCTGACCAAGGGAGCC +>SERBP1_K562_rep01_1908 +CCCCGCAAGCCACCACCCCGGAAGCACACTCGTTCCTGGGCTGTGCTGAAGCTGCTGCTGC +>SERBP1_K562_rep02_310 +AAGTACCTGGCTTTCCTCCGCAAGCGGATGAACACCAACCCTTCCCGAGGCCCCTACCACT +>SERBP1_K562_rep01_292 +CTTCCTCCAGTCGGTGCACCGCTGCATGACCTCCAGGCTGCTGCAGCTCCCGGACAAGCAC +>SERBP1_K562_rep01_903 +GCAGGCCGGGGAGGCAGAGGGCGCTCAGGCCGTCACCCAGCTCATGGTGGACCGGCTGCCC +>SERBP1_K562_rep01_698 +GCAGAGCCCCATGTGTCAGGTGTGAAACGGTCCCGCTCAGGTGAGGGCGAGGTGAGCGGCC +>SERBP1_K562_rep02_843 +AGGAGGCTGCTGAGATGGGAAAGGGCTCCTTCAAGTATGCCTGGGTCTTGGATAAACTGAA +>SERBP1_K562_rep01_2537 +CCACCTCTGCCCCCGGCCTGGCCTGGGGGCCTCTGGTGCTGGGCCTCTTCGGGCTCCTGGC +>SERBP1_K562_rep02_1214 +TCTTCGCCAGGCCAGGAATCACAAGCTCCGGGTGGATAAGGCAGCTGCTGCAGCAGCGGCA +>SERBP1_K562_rep01_1226 +CAGAAGGAGTACAAATGCGGGGACCTGGTGTTCGCCAAGATGAAGGGCTACCCACACTGGC +>SERBP1_K562_rep01_2295 +AGATGCACTCCCCTCAGACTTCTGCCATGCTCTTCACGGTGGACAATGAGGCTGGCAAGAT +>SERBP1_K562_rep01_3286 +GAAGGTAAAGGCAGACCGAGATGAATCCTCACCATATGCTGCTATGTTGGCTGCCCAGGAT +>SERBP1_K562_rep01_483 +TCGCTGGACTGCTCAGGGTGCCAGACCTCATCCATTCCAAAATATGCCCGGTGCTATCCGC +>SERBP1_K562_rep01_2019 +CCAACGAGGCAGAGCGCCGCCCGGCGCGAGACTGCGGCCGAAGCGTGGGGCGCGCGTGCGG +>SERBP1_K562_rep01_3050 +AGAGCACTGTCCGGTGGTGCCCAGGAGGAGTAGGAGCAGGAGCAGAAGCAGAAGCGGGGTC +>SERBP1_K562_rep01_1330 +AGAGAGTGGGTATTTTACTGGATGAAGCCTCAGGTGTAAACAAGAATCAACAGCCTGTCCT +>SERBP1_K562_rep02_1347 +GGTACGGGCCTGGGGCCCTGGGCTGGAGGGCGGCGTCGTTGGCAAGTCAGCAGACTTTGTG +>SERBP1_K562_rep01_2212 +CCACGGAGGCAGTGGTGGCGGCCCTGGCTGGACCACGCCACAGTCATCCACTCCGGGGACT +>SERBP1_K562_rep02_415 +GGGCCCCGCAGCAGGGGCCGGAGCCGCCGGCGGCGGGGCGGGGGGGGGCGCCCCGATGAGC +>SERBP1_K562_rep01_2699 +TGACAAGTTCATTTTCCATAAGGATCTGTGCCAAGCTCAGGGTGTAGCGCTGCAAACAATG +>SERBP1_K562_rep02_1474 +GTTCCGTGCCATTGAAGTCCTCAGTCTTGCCCTCACCATCAGGACGATCTGCTCAGGGCAG +>SERBP1_K562_rep01_472 +CCCCATGGCCTGTCAGGAAGATCCCGCTGCGCTGCACGGCCCACTATGTGGCTTACCACGT +>SERBP1_K562_rep01_282 +ATGCACTCCAGAGCCTGACTGGCGGACCTGCTGCGGGAGCCGCTGGAATTGGCATGCCTCC +>SERBP1_K562_rep02_654 +GCAGCACCGAGGCTTCCTCCTCCTCACCCTCCTCGCCCTGCTGGCGCTCACCTCCGCGGTC +>SERBP1_K562_rep02_486 +AATCATGCTGCCAGTAAGAAGCTTGACCTGGAGGCCTGGTTTCCGGGCTCAGGAGCCTTCC +>SERBP1_K562_rep02_718 +CCACTCTGAGAGCAAACCCATCTGCGCCGTCGGCCACGGTGTCGCCGCCCTGTGCTGTGCC +>SERBP1_K562_rep01_26 +CCACCCGCCTGGGTACCCTATCACCTGCCTTCAGCACTCGGGTGCTGCCAGCTCAAGCCAC +>SERBP1_K562_rep02_759 +CTTAGATAAGAAGGTTGAGAAGGTGACAATCTCCAATAGACTTGTGTCTTCACCTTGCTGC +>SERBP1_K562_rep01_205 +TGAGTTGGCTGCAGCACAGAGATTGCTGGCCCGGGTGCAGGAGCAGCTGAGCAGCCTCTGG +>SERBP1_K562_rep01_2169 +CGGAGGAGCCCAGAGGGTCCTCACTGAGCAGCGAGTCGTCCCCCGTGTCCTCTCCGGCCAC +>SERBP1_K562_rep02_295 +GAGCTGAATAAGCGGGGCCGTGTGCTGGTCAATGATGCCCAGAAGGTGACTGAGGGGCAGC +>SERBP1_K562_rep01_1893 +GTGCATGGAGTGCTTCCGGGAAGCCGCCTATACCAAGAGGCTCGGCACAGAGAAGGAGGTC +>SERBP1_K562_rep02_1157 +ACCAGATGGCCAGGGTGAAGGTCGCCGCCTGCAACGTGCACTCCACCTGTGGGGACTGCGT +>SERBP1_K562_rep02_1071 +AACTGGCCACCCAGCTGACCGGACCGGTCATGCCCGTCCGGAACGTCTATAAGAAGGAGAA +>SERBP1_K562_rep01_1267 +GGCCAAGCTCGGCCATCTACCCCTCCGACAGCTTCCGGCAGTCCCTCCTGGGCTCCCGCCG +>SERBP1_K562_rep01_676 +TGGAAAGCATTCCTGAGGGCCTGGACTTCCCCAATGCCTCCACGGGGAACCCTTCCACCAG +>SERBP1_K562_rep01_2840 +AGTGGGGAGCTGAAGGTCACCGTGAAGGGCCCCAAGGGAGAGGAGCGCGTGAAGCAGAAGG +>SERBP1_K562_rep01_1733 +TCATCAATGACAACACCGCCACTGCCCTCAGCTATGGTGTCTTCCGCCGGAAAGATATTAA +>SERBP1_K562_rep02_559 +CGTGAACGAGAAGTCCTGCAACTGCCTCCTGCTCAAAGTCAACCAGATTGGCTCCGTGACC +>SERBP1_K562_rep01_23 +GCCGGCACTGGCGATGTTGCTGTGGTGATCGTGGACCCACAGGGCCGGCGGGACACAGTGG +>SERBP1_K562_rep01_2958 +TAAACCTGGAGTTGATTATACCATCACTGTGTATGCTGTCACTGGCCGTGGAGACAGCCCC +>SERBP1_K562_rep01_1615 +TCGGCCGGTTTTGAGAGGGGAAGATGGGGACAAAGCCGCTCCACCTCCCATGTCGGCACAG +>SERBP1_K562_rep01_1 +CCTGTGCCTGCCAGTCGGTGCCCCTCCCGCTCCAGCCATGCTCTCCGCCCTCGCCCGGCCT +>SERBP1_K562_rep02_1409 +GCCTCCGCCGGAGCCGCCTCGTGCACTCTGGGGTATGGCCGTCAATGTGTACTCCACATCT +>SERBP1_K562_rep01_2382 +TCTTCAATCACCTCGACTCGCAGGGCAACCCCTACTATGCCAACCCCGCTCACGCGCGGGC +>SERBP1_K562_rep01_2279 +AGAGAAGACGAAGCAGTTCATCGACAGCAACCCCAACCAGCCTCTTGTCATCCTGGAGATG +>SERBP1_K562_rep02_357 +CCGGCTGACCTGCCCAAGCTGGTGGAGGGGCTGAAGCGGCTGGCCAAGTCCGACCCCATGG +>SERBP1_K562_rep01_1367 +CCGAGAAGCTAAAAATAAGAGGCGATCTGGAAAGAATTCACAGGAAGATAGTGAGGACTCA +>SERBP1_K562_rep01_2177 +GCCGCAGCCGCCGCCGCCGCAGCAACACCAGGAGAGGCCGGGGGCAGCCGCCATCGGCAGC +>SERBP1_K562_rep01_2409 +TCCACCAGCAGGGCCCCGCGGAGCTCCCCCCGCTGCCCCCTACCACCCCTTCACTACCCAC +>SERBP1_K562_rep02_1106 +ATGACCCCTCTGGGCCTGCTGGCTCCCTGACTTCTGTTGAGTTCTGTGGGGGAACGCACCT +>SERBP1_K562_rep02_948 +GAGTGCTTTCACCCGAGTAGCATCAATGGTTTCCCTTCAGCCCGCAGAGACCCCAGGCATG +>SERBP1_K562_rep02_519 +TGGCTTGAGGCTGTCATCTTCCTCATCGGTATCATCGTAGCCAATGTGCCGGAAGGTTTGC +>SERBP1_K562_rep02_227 +CGCCAGACCGCCGCCGCGCCGCCATCATGGACACCAGCCGTGTGCAGCCTATCAAGCTGGC +>SERBP1_K562_rep02_846 +GACCCACCAATGGAAGCAGCTGGCTTCACTGCTCAGGTGATTATCCTGAACCATCCAGGCC +>SERBP1_K562_rep02_1198 +TGGGGTGAGGCCCTCACTTCATCCGGCGACTAGCACCGCGTCCGGCAGCGCCAGCCCTACA +>SERBP1_K562_rep01_935 +CCTCATGACCCAAGCAAAGCAGCTGCAGCGGCCGCGGACCCCAACGCCGCGTGGGCCGCCT +>SERBP1_K562_rep01_2221 +AAAGCCAGCGAGTGGGTGCAGCAGGTGTCAGGCTTGATGGACGGTAAAGGTGGTGGCAAGG +>SERBP1_K562_rep01_719 +GGACTCTGGGCTGGGAAGCCCTGTTGGCCCGGCGCCTGCCACCGCCCTTTGTGCCCACGCT +>SERBP1_K562_rep02_892 +GCGGCGGCGGTAGAGGCGGCGGCGGCGGCGGCAGCGGGCTCGGAGGCAGCGGTTGGGCTCG +>SERBP1_K562_rep02_1358 +CCAAGGATGCAGGAGAGGGGGGCCTGTCTCTGGCCATTGAGGGCCCGTCCAAAGCAGAAAT +>SERBP1_K562_rep01_2630 +GGAGATGGTGCGTGCCCAGAACAAGAAGAAGAAGAAGTCTGGAGGCTTCCAGTCCATGGGC +>SERBP1_K562_rep01_1530 +GACGCGGCGTTGCCACCAGGGGCCAATTAAGCCTTACCAGCAGGGGCGACAACAGCATCAG +>SERBP1_K562_rep01_1310 +ATGCTCATGGAAGATGTGGGCAGTGAGGAAGAACAAGAAGAGGAGGATGAGGCACCATTCC +>SERBP1_K562_rep02_1186 +GCCGCCGCAGCTGCTCCTGGTCCCCGTCCCTTTGCCGCCCTCGTCAGGCCCAGCTCTCCTG +>SERBP1_K562_rep01_230 +TCTCCAGCTCTATCAGATCACCCAGATCAATCATGGCCTGATGATGGTGGGGCCCTCGGGA +>SERBP1_K562_rep01_2529 +ACAGCCTCAAGATCATCAGCAATGCCTCCTGCACCACCAACTGCTTAGCACCCCTGGCCAA +>SERBP1_K562_rep02_1449 +GCAGAGCAATCAGGCTGGAGTTGCAAGGACCCAGGGGATCACCTAATGCCAGAAGCCAGCC +>SERBP1_K562_rep01_1272 +ACTGCGTGTGGAGGTACAACTCAAGCGTGAATGAGTGGGCGGAGGTGGCGCCCATGCTGAA +>SERBP1_K562_rep01_170 +CCACACGCCAACCCCGTTCAAGAACGCCCTGGAGAAGTACGGACCCCTGAAGCCCCTGCCA +>SERBP1_K562_rep01_1484 +AAGTTTTATTGTGACTACTGCGATACATACCTCACCCATGACTCTCCATCTGTGAGAAAGA +>SERBP1_K562_rep01_56 +GGCTGTCCCATCGACATCAAGGTGATCCCCAACGGCGACGGCACCTTCCGCTGCTCCTACG +>SERBP1_K562_rep01_1725 +AGAGACTGAGGGGAAGAGAGGAAGGAGGGGCGGGCTCCTGGCAAGGCATTCGCTCCTGAGC +>SERBP1_K562_rep02_200 +AGGGCCCCCCTAAGCGCGTGTCCCTGGTGGGTGCTGACGACCTGCGGAAGATGCAGGAGGA +>SERBP1_K562_rep02_302 +GACATGTCCTACGAGCAGCTGATGCAGCTGTACAGTGCGCGCCAGCGGCGGCGGCTGAACC +>SERBP1_K562_rep02_553 +GGAATCCCACTGTTGAGGTTGATCTCTTCACCTCAAAAGGTCTCTTCAGAGCTGCTGTGCC +>SERBP1_K562_rep02_1037 +AGCCCCACTTCCACAAGGACTGGCAGCGGCGCGTGGCCACGTGGTTCAACCAGCCGGCCCG +>SERBP1_K562_rep01_2108 +ACCATCTCTGAGCTTGCGTCATGCCTGCAACGGGCCCGGGAGCTGGGGGCAAGAGTCCGGG +>SERBP1_K562_rep01_2026 +GACGAAGGCCGTGTGCGTGCTGAAGGGCGACGGCCCAGTGCAGGGCATCATCAATTTCGAG +>SERBP1_K562_rep01_409 +TACAAGTATCTCAATCAGACCAGTCGCAGTTTCGCAGCTGTTATCCAGGCGCTGGATGGGG +>SERBP1_K562_rep01_3251 +AATTCCACCAAGTTCTCCCTCTTTGCTGGAGGCATGCTGAGAGTTCACCTGGACATCCAGG +>SERBP1_K562_rep01_2723 +CAGACAAGTTCAGCATATTTTAGCATCAGCCAGTCCCAGTGGCCGGGCCACTGTATGGGAT +>SERBP1_K562_rep01_84 +CGTCTTCAGTGGTTCTCGTCTCAAACTCTATTTGCCAAAGGAAACTTGCCTTATCACCTTC +>SERBP1_K562_rep01_3236 +GATAGCTGGCCAGAGTGCCCGGGCGATCATGGCTCAGCTTCCCCAGGAGCAAAAAGCGAAG +>SERBP1_K562_rep01_1949 +CTTTGGAGAACTGTGCCCCAACACCGCCCCATTGCCCCAGCTGGTGACTGAGGCCCTGCAG +>SERBP1_K562_rep01_1506 +TGGCCCAGGCTGCCAGCGCCGCTGTGACTCGGGGTGACCTCCGCATCCTGCCTGAGGCCCA +>SERBP1_K562_rep02_335 +CCCTATTCTGTCACGAACCCTGCCGCCCCCTGCATCAGCTGGCTACCGACTCCACCTTCTC +>SERBP1_K562_rep01_575 +TGCTGGCCGCTGGGATGTCCTGATCCAGCAGGCCACCCAGTGCCTCAACCGCCTCATCCAG +>SERBP1_K562_rep01_512 +CGCACGGCCCCGGGCCTGAGCCCTGGCACCCGCTGGCCGCCCACCCGCGCCCGCCACTCGG +>SERBP1_K562_rep01_1029 +CGGCCGGGAGCTGCTCTGTGCTTTTCTCTCTGATTCTCCAGCGACAGGACCCGGCGCCGGG +>SERBP1_K562_rep01_1767 +GAGACACGCCGAAATCCGCCCGAGGCTACCTGTGCGACTCCAGCCGCCCTGCACCGGAAT +>SERBP1_K562_rep01_2662 +ATCGCTTGCCCTGCCGGGATGACGATAGTGTGACTGCCAAAGATCTTAGCAAGCAACTCCA +>SERBP1_K562_rep01_794 +CGCAAACTGACACCTCAGGGACAAAGAGATCTGGACAGAATCGCCGGACAGGTGGCAGCTG +>SERBP1_K562_rep02_886 +GGTTTGTTTGGCAGCTGTGGGCTTAGTGGGAGACTTGTGCCGTGCCCTGCAATCCAACATC +>SERBP1_K562_rep01_3183 +GCTCATTCACTGTGTAGGTCCCGTTTCCCTCTGTGCGGCGGCCGGCGGGACCATAAGGGCT +>SERBP1_K562_rep01_2937 +CGCTGCACCCTCTCGGCTAATCTCGTAGCCTCAGGTGAACTGATGAGTTCCAAGAAGAAGG +>SERBP1_K562_rep01_560 +CCGGGCCGCGGCTGTGGGGAGGGCGACGGAGCGGGTGACCTTCCGGAGGCGGGAGCGAGCG +>SERBP1_K562_rep02_315 +ACCATGGACAAGGCAGCTACTCCTACTCGAACTCCTACAACTCTCCCGGGGGCGGGGGCGG +>SERBP1_K562_rep02_943 +TCTGGGCAAAGATGTCAGTGGGTTCAGCGACCCCTACTGCCTGCTGGGCATTGAGCAGGGG +>SERBP1_K562_rep01_767 +ATGTTGTGGGTATCACTTACCAGCACATTGACCGCTGGCTGCTGGCCGAGATGCTCGGGGA +>SERBP1_K562_rep01_3119 +CTCCATGGGTGATGCTGGGGAGATGGTGCGACAGGCCCGCATCCTGGCCCAAGCCACATCT +>SERBP1_K562_rep01_2422 +CACCTGGATTCCCTTCCTTCAATCACACTCAGTTTCCACCATCTCGGTCATCAGGATTGCC +>SERBP1_K562_rep02_876 +CTCCGGTTGTCGCCGGGCGGGCCAGGAGCAGCGCGGACCCGAGCCGGGCAGGGGGCGCCCG +>SERBP1_K562_rep01_433 +CAGGAGCCCACGGTGCATTTCGCAGAGGACGCACTGCTGCCCGGGGATGACAGGGAGATCG +>SERBP1_K562_rep01_1335 +CCACCTGGAGTTCCGCTATGAGTTGGGGTCAGGGCTGGCCGTTCTGCGGAGCGCCGAGCCG +>SERBP1_K562_rep01_928 +CCTGGCTCCCACTCAGAGAATGCGCTCCACGCCAGTGAGGAGGAGGAAGGCGAGGGAGGCA +>SERBP1_K562_rep01_463 +GTTCGCGGGGTGCGGGGCGCACGGCGGCGCCGAGCGTGCGGCCGGAGAAGCGGCGGTCTGA +>SERBP1_K562_rep01_1325 +GAGCAGTGCTTGGCTCCCTGCAGTTTGGCTACAACACTGGAGTCATCAATGCCCCCCAGAA +>SERBP1_K562_rep01_3051 +AGTGCGCGGAGCTGCGGCGGTGGAGCTGCTCGGCCGGGAGCCCGGCGGCG +>SERBP1_K562_rep02_895 +CTGGGTCCGATACGCCGAGCGGGTGCTGGGTCGCCCCATCACTGCCCACCTCTGCACCGCC +>SERBP1_K562_rep02_206 +ACGTGGCCGCCGGGACCTGCCTCATGCAGGGGGAGGAGGTCACGTGCCGAGGGCGGATCTT +>SERBP1_K562_rep01_267 +CTCAGCAGGGGGATCATTCACAGTGAGGACAGACACAGGTGAACCTATGGGTCGTGGAACA +>SERBP1_K562_rep01_2130 +CGGGAGACGCCCCCCAGCCACAGCCCACCTGCTGAGGGGGACCCCCGCACCCACCAGGTAC +>SERBP1_K562_rep01_1418 +AAGCTTTCTGCACTACACCGGAGAGGGGAGCCGCGATCCGGCCGCGCCGCCCGCACGCCGC +>SERBP1_K562_rep02_721 +TGAGACCCTGTGCGGCGGGGAGCTGGTGGACACCCTCCAGTTCGTCTGTGGGGACCGCGGC +>SERBP1_K562_rep02_1111 +TCGGCAAGTGGCCCCCGAGTCACACTGGCCTGAACTCCGCGTGCTCATCCTTGTGGTGAGC +>SERBP1_K562_rep01_1220 +CGCTTGGCCCGGCCCGCAGGTAGGAGCCGCCGAGGGACGCGGCGCCCGGTTCCCGGCCCCG +>SERBP1_K562_rep02_1056 +GCCGCTTCCTTTCCGCTCGGCTGTTTTCCTGCGCAGGAGCCGCAGGGCCGTAGGCAGCCAT +>SERBP1_K562_rep02_333 +AGAACATATTCCCGCCCTCGGCCACGCTGCACCTCTCCAACATCCCGCCCTCAGTCTCCGA +>SERBP1_K562_rep01_738 +ACAGGAACCTGTGGCCCTTCGTATCCGACCCCGCCCCCACGGCCAGCTCCCAGGCCGCTGT +>SERBP1_K562_rep02_1552 +GCTGCCGCCACCGCATCGCGCAGCTCTTTGCCGTCGGAGCGCTTGTTTGCTGCCTCGTACT +>SERBP1_K562_rep02_1534 +CCCTTCATGGCCAACATCCCTCTCCTCCTCTACCCTCAGGACGGCCCCCGCAGCAAGCCCC +>SERBP1_K562_rep01_3053 +CGGCGCCAAGTTTTGGGAGGTGATCAGCGATGAGCACGGCATCGACCCCACGGGCACCTAC +>SERBP1_K562_rep01_2641 +ACCAGATGGTGAGGAGAGGCTTGGGGGAGAGGCTCACTCCATGGTCTGGGACCCCAGTGGG +>SERBP1_K562_rep01_1610 +AGGAGGGCTTGCTGTGCGGAGGGCCTGCTATGGTGTGCTGCGGTTCATCATGGAGAGTGGG +>SERBP1_K562_rep01_3299 +ACCTGCTGATGAGTGCAACAAGCTGAAAGAAGAGATTTCCAAAATGAGGGAGCTCCTGGCT +>SERBP1_K562_rep02_1250 +GGCGCTGGGGACCCGCGGGGGCTGCGCCGCGCCCGCACCCGCGCCGCGCGCCGAGGACCTC +>SERBP1_K562_rep01_1486 +GGAGGAGCAGATCACGCTTGCGAAGGCGGTCTCGATCACGCGGTGGTCGTAGACGAAGGAG +>SERBP1_K562_rep01_1159 +AGCTGCTGTGACCCCTGCAGCCATTGCAGCTGCCACAACCACATTAGCACAGGAAGAGCCA +>SERBP1_K562_rep01_1131 +AGTAAATGCCGGCTTACCATCTCTACCATCATCCGGTTTAGTCATCCAACAAGAAGAAATA +>SERBP1_K562_rep01_3264 +GGCAAACACCTTTACACGCTAGATGGTGGGGACATCATCAACGCCCTGTGCTTCAGCCCTA +>SERBP1_K562_rep02_263 +CCCAGGCACAGCCGACGCCGCGGGCGTCTGACCAAACACACCAAGTTCGTGCGGGACATGA +>SERBP1_K562_rep01_2498 +GCTGACACATTCCTGGAGCACATGTGCCGCCTGGACATTGATTCACCACCCATCACAGCCC +>SERBP1_K562_rep01_1744 +TACTGATACTGTCCAGGAGGAAGAGGAGAGCCCTGCAGAGGGGAGCAAGGACGAGCCTGGG +>SERBP1_K562_rep01_3029 +CGGTAGCAGTAACCTCTGTGTGCTGGAGCCCCAAAGGAAAGCAGCTGGCAGTGGGAAAACA +>SERBP1_K562_rep01_478 +GGCTTTGTGCGCGGCGGCGGCGGGAGAGGCGGCGGCGGCGGCCAGCACGGAGGCGGAGGCC +>SERBP1_K562_rep01_2273 +ATCGCCGAAGCTTCGGGAGTTAGAACCGGGACAAAAATCATCATCCACCTGAAATCCGACT +>SERBP1_K562_rep01_2628 +CCCCGTTCACAATGCAGCCTGCTTCTGCAAAGTGGTACGATCGAAGGGACTATGTCTTCAT +>SERBP1_K562_rep02_589 +TCAATGGGACCTCCCAGGGCAAGTTCCAGGGCCTGGATCTGAACGAGGAACTCTACCTGGG +>SERBP1_K562_rep01_1646 +GGAAACGTCTGTGTGAGAACATTGCCGGCCACCTGAAGGATGCACAAATTTTCATCCAGAA +>SERBP1_K562_rep01_578 +GAGTTCCTCGCATCCACTCAGAGGAAGGAGTTTGGGGACACCGGGGAGGGCTGGGAGACAG +>SERBP1_K562_rep02_380 +CGTGCACAAGGTGAAGCCCACCTTCAGCCTCCCGCCGCAGCTGCCGCCCCCGGTCAACACC +>SERBP1_K562_rep01_614 +CCGTGGCGGCTTCCAGAACCGAGGGGGAGGCAGCGGTGGAGGAGGCAACTACCGAGGAGGT +>SERBP1_K562_rep01_402 +CGCCTGCGCACCGGCACCGACGCGGAGCGACCCAGCCCAGCCAGACCCGGCCCGGCGCGGC +>SERBP1_K562_rep02_147 +GGCGGCGGCGGCGCCCAATGGCAACAGCAGCAGCAACTCCTGGGAGGAAGGCAGCTCGGGC +>SERBP1_K562_rep01_3294 +TGTGGGATGCTGGGATCAAGGCTGAGCTGCTGTACAAGAAGAACCCAAAGCTACTGAACCA +>SERBP1_K562_rep02_923 +CTCGTGTTGACTTCTCGCTCCGGGATCCGGACAGGCTACCAGGCCAAGCAGGTCCGCCGGT +>SERBP1_K562_rep01_1289 +ACTTTCTGGGCATCAGCATCGTGGGGCAGAGCAACGACCGTGGAGACGGCGGCATCTACAT +>SERBP1_K562_rep02_1337 +GAGATTGTGGTTATCACCACCAAAGGAGAAGCAATCTGCATGGCTATTGCATTAATGACCA +>SERBP1_K562_rep01_886 +TATATGTTCTTCAACACATCAGAGCTCCGAGAAGCGGTACCTGAACCCGTGTTGCTCTCCC +>SERBP1_K562_rep01_517 +TCCCCTTGTCCCCAAGAGACCCGACGCTTGCTTCATGGCCTACACGTTCGAGAGAGAGTCT +>SERBP1_K562_rep01_1221 +GCAGCCACCGCCACCCATTGGAATGGCCAACAGGGGACCTGCATATGGCCTGAGCCGGGAG +>SERBP1_K562_rep01_2027 +GACGGACAATGAAGTGGCCGCCTTGCAGCCCCCCGTGGTGCAGCTGCACGACAGCAACCCC +>SERBP1_K562_rep01_1270 +CGAATCCAGAACTTGGACCAGAGCTGCCAAGGGACGTATATATGCCAGGCCCATGGACCTT +>SERBP1_K562_rep02_627 +CAGTTCGAGGCCGCTGCGCGGCCCTGCGCATGCTGCTGGCAGATCAGGGCCAGAGCTGGAA +>SERBP1_K562_rep02_117 +GCCGAGAGGCCGCGGAGCCAGCGACGACCGACCCAGCCGAGCCGCCGCCGCCGCCGCGCCC +>SERBP1_K562_rep01_1627 +GGAGGGAATGGAGGAGGCGACCGTTGTTATCGAGCATTGCACTAGCTGACGCGTCTATGGG +>SERBP1_K562_rep01_711 +CAACCGGGGAGACAGCCTGAGCCGGCACGCCCGGCCTCCCGACCCCCCCGCTAGCGCCCCG +>SERBP1_K562_rep02_1253 +AGTGGGCGGACCGCGCGGCTGGAGGTGTGAGGATCCGAACCCAGGGGTGG +>SERBP1_K562_rep01_785 +GCCGGGGCTTCTTCCGTGGGGGCCGAGGACGGGGCCGTGGGTTCTCTAGAGGAGGAGGGGA +>SERBP1_K562_rep01_201 +TATGGGTCCCCCAATGGGGATCCCCCCTGGAAGAGGGACTCCAATGGGCATGCCCCCTCCG +>SERBP1_K562_rep01_2113 +AAGTATATCCCTCTGCCTCAACGAGTCCGGGAAGGTCCCCGGGGAGGAGTTCGATGCAGCA +>SERBP1_K562_rep01_427 +CTGCTGTTGCCACCACCAGCATAACCACTGCCACCCCCGGGGTGCCTGGGTTGCCGAGCCT +>SERBP1_K562_rep01_1914 +AGCTCAACTACTCCTTGGTGCAGAAGGTCGTGACACGCTTCCCTCCAGTGCCCCAGCAGCA +>SERBP1_K562_rep01_974 +CAGCCCCCAAGATCGCAGCTTCATCGTCTTTCCGATCTTCCGACAAGCCCATCCGGACCCC +>SERBP1_K562_rep01_696 +AGAGGGGACGTTCCACAGACAGTGAAGTCAGCCAGTCTCCAGCCAAAAACGGCTCCAAGCC +>SERBP1_K562_rep01_1462 +CCAGGAGCGATATGGTTCTCGCCCCGTCTGGGCTGACTACCGCCGCAACCACAAGGGTGGT +>SERBP1_K562_rep01_2109 +GTTCTCCCAAGTCTGCTGCCCCTGCCCCAATCTCAGCTTCCTGTCCAGAGCCTCCCATCGG +>SERBP1_K562_rep01_385 +AGATGGCCCAATCTGTCTAGTTCTGGCTCCTACCAGAGAGCTTGCCCAGCAAGTACAGCAG +>SERBP1_K562_rep01_2684 +CGGCCGTCTCAGGAGCCGCAGCGCCCGCGGGCCCGGGTGCGGGCCCGGCGCCGCACCAGCA +>SERBP1_K562_rep01_1602 +TACCACATGCTGAGCCGGCCCCAGCCGCCACCCGACCCCCTCCTGCTCCAGCGTCTGCCAC +>SERBP1_K562_rep02_1450 +GAAAGAAGGAAATGGCCAAACAGAAAGCAGCTCCTGAAGCCAAGAAACAGAAAGTGGAAGG +>SERBP1_K562_rep01_2827 +GCCCACAGATGAGTGGGATGGCCGCACTGGCCGCTGCGGCCGCTGCCACCCAGAAGATCCC +>SERBP1_K562_rep01_984 +GCTCTGTGCCGGGCGCTGTCAGCTGTCCACAGCCCCACCTTCTGCCAGCTGGCGTGCGGCC +>SERBP1_K562_rep01_549 +AGCTGACTGTCGGGAGAATGTGATCATGTCCCAGATCTTGCCCTGCATCAAGGAGCTGGTG +>SERBP1_K562_rep01_619 +GCGAGCAGAAGGAGGACGTGCAGCACAGCATCATCACCGACCTGCAGAATGGGAACGACCA +>SERBP1_K562_rep01_1605 +GGCAACTGAAGCCTTTTGAGACCCTGCTGTCCCAGAACCAGGGAGGCAAGACCTTCATTGT +>SERBP1_K562_rep01_1777 +AAAGAAGTTAACTGGGGGATCTAACTGGCAACCAAAGGTTGCACCAACAACCGCTTGGAAT +>SERBP1_K562_rep01_567 +CTTCATCACAGCTGAGGAGCTGCGGAGAGAGCTGCCCCCCGACCAGGCCGAGTACTGCATC +>SERBP1_K562_rep01_2604 +TACAGAGCAGAGCAGCGGCAGCAGCGGCGGGGGTGGGGGCAGCAGCAGCCGCCCCGCCTCC +>SERBP1_K562_rep01_2896 +TGCCACAGCTTGCTGATGCTGGCCGGGGTAGTTGTTAGCTGCCAGGACATCACTCCAGACC +>SERBP1_K562_rep01_2411 +TACATAACTTCCTACGTATCCTGCAGCGGGAGGAGGAGGAGCACCTCCGCCAGATCCTGCA +>SERBP1_K562_rep01_1164 +CAACTGGCAGCTTTGAAAAAACACCATGAAGAAGAAATCGTTCATCATAAGAAGGAGATTG +>SERBP1_K562_rep01_825 +CCGCTGCCGCCGTCGCCGTCGCCGCCACCGCCGCCACCGCTACCGAGGCCGAGCGGAGCCG +>SERBP1_K562_rep01_1019 +GCGAGAGGAGCAGCTGGCACGGGAGGCCGAGGCCCGGGCGGAGCGGGAGGCGGAGGCCCGG +>SERBP1_K562_rep01_973 +GGTTGTGTTGAAGAGGTTGTTTATGAGTCGCACCAACCGGCCGCCTCTGTCCCTTTCCCGG +>SERBP1_K562_rep01_1750 +AGCGTGGGCAACGTGAAGGAAGTGGACCGGCGCAGCTTCGACCTCACCACGCCCTACCGCA +>SERBP1_K562_rep01_2292 +TCGCTGACCTTGGAGAGGCCCTGGCCACTGCAGTCATCCCCCAGTGGCAGAAGGATGAATT +>SERBP1_K562_rep02_305 +AAGCTGCGGGTCAGATTCCAGCCACTGCTCTTCTCCCCACCATGACCCCTGACGGTCTGGC +>SERBP1_K562_rep01_273 +GGGCATCCTCCTGCTGGCAGGCCTGTGCTGCCTGGTCCCTGTCTCCCTGGCTGAGGATCCC +>SERBP1_K562_rep01_587 +CAGTTCCTGCCGCCCAACCTTCTGGCCCTCTTTGCCCCCCGTGACCCTATTCCATACCTGC +>SERBP1_K562_rep02_19 +GGCATCCCTCGGGCGGCGGCGGCGGCGGCGGCGAGGCGAAGCGAAGGAGGA +>SERBP1_K562_rep01_593 +CAAGAACAACCAGTTCCAGGCCCTGCTGCAGTATGCGGACCCCGTGAGCGCCCAGCACGCC +>SERBP1_K562_rep02_341 +AGAAGAAGGTCAAATAAGGTGGTTCTTTCCTTGAAGGGCAGCCTCCTGCCCAGGCCCCGTG +>SERBP1_K562_rep02_575 +GGTGTGAATGTGACAATGCCTGCGCAGCCCGGCACGCCACCCCTCTCCTCCACGCAGCTGC +>SERBP1_K562_rep01_2614 +GGCTGCATTCCCGCCCGTGGTGGAGGATGAGGAGATGGAGGCGTCGGGCGTGAGCGGAAAT +>SERBP1_K562_rep02_996 +CCCCCTGCACCCACCGCCACCGTGCCTGCTGCTGCTGCACCCGCTGCTGCCTCTCCTCCTC +>SERBP1_K562_rep02_1420 +GGAAGGAATTCCTCCTGATCAGCAGAGACTGATCTTTGCTGGCAAGCAGCTGGAAGATGGA +>SERBP1_K562_rep02_144 +CCTCCCGTCCCTGCGCGGCCTCGGCGGCCTCGGCGGCGGCGGCGGCGGCGGCGGCGGCAGC +>SERBP1_K562_rep01_1299 +GCCACCACTGATGCCACCCAGGACCTCGGACCTTGGAGCCTGCGGGGTGCCTCGGCCCCTC +>SERBP1_K562_rep02_338 +AAAGGGCCCGCGCGTTGCCGCCCCCTCGGCCCGCCATGCTGCTATCCGTGCCGCTGCTGCT +>SERBP1_K562_rep01_565 +TCTCCCTATGCTGCCCCCTCCCCACAAGGTTCCTACCAGCCCAGCCCCAGCCCCCAGAGCT +>SERBP1_K562_rep01_2665 +GGAAGAGGCCATGCACGCCTGGTGCATGTTGAAGAGCCTCACACGGAGACCGTACGAAAGT +>SERBP1_K562_rep01_906 +CTTCCTGTGCCTGCTGGACGAGCGCGAGGTGGTGCGGATGCTCCTGCAGGTCCTGCAGGCG +>SERBP1_K562_rep02_352 +CTCTTCCGCCGTCGTCGCCGCCATCCTCGGCGCGACTCGCTTCTTTCGGTTCT +>SERBP1_K562_rep02_1330 +GGAAACCATCACAGCTTGCCTGTGGGGACCACTCAGCCTGTGGGTGGTGATCGCCTTTCTC +>SERBP1_K562_rep01_2020 +TCCTCAGGGGTGAGGCTCTGGGCTACACGCCAGGCCATGCTGGGCCAGGTGCACGAGGTTC +>SERBP1_K562_rep01_41 +GACGCACGGGACGCGGGCGAGGGGTTGCTCACTGTCCAGATCTTGGACCCCGAGGGTAAGC +>SERBP1_K562_rep02_368 +GACCCTGAAGACGGCTGTGGACGGGCCTGACCTGGAGATGCTCACGGGGCAGGAGCGCGTG +>SERBP1_K562_rep01_1356 +GTGTGGCAACGTGCATGGCCATCCTCCATGTGGGTAGTGCCCAGCAAGTGCGGACAGGGTC +>SERBP1_K562_rep01_1807 +TTCCGTGGCGTGGCCTTCGTGGGCGGCTTCAGCTATGCAGATGTCCTGGGCTCTGCCAAAG +>SERBP1_K562_rep02_1052 +GCCGGCCCCCGGTGCCGGCGGAGGCAGAGCACAGGCCGGAGAGCACCACCAGGCCAGGACC +>SERBP1_K562_rep02_444 +TCGATGTACATTTCGAGCAGCGGAAGAAGGAGGAAGAGGAGCTGGTTGCCTTGAAGGAGCG +>SERBP1_K562_rep01_3164 +GCCCGCCTGTCCCGCTCCCTCCCTCCCGGGGACCCGGAGGAGAGGGGACCATGCCGGAACC +>SERBP1_K562_rep01_1845 +TAAGGATGTCTTCAGAGATCCTGCTCTTAAACGCAAGGCCCGACGGGAGGCCAAGGTCAAG +>SERBP1_K562_rep02_1329 +GGTTCGAGATTCTCCCCGGACTCTCCGTCATGGGCGTGTGCTTGTTGATTCCAGGACTGGC +>SERBP1_K562_rep01_1888 +CTGGCCACGGTCACCTGTATTCCCGCATCCCAGGCCTGCTCAGCCCCCATCCCCTGCTGCA +>SERBP1_K562_rep01_1563 +GCTGTTCCTGATGTATACAGTGCTTGTAAAAGGTTTGAAGAACTGGGAGTCAAATTTGTGA +>SERBP1_K562_rep01_2268 +GCGTGGATATGTGTTGAGACGGATTCTCCGCCGAGCTGTCCGATACGCCCATGAAAAGCTC +>SERBP1_K562_rep01_66 +GAGCAAGCCATTGACAGAGAACATGAGAGAGATGTATTCCAACAGGAAATACAGAAACTAG +>SERBP1_K562_rep01_1626 +GGTGAACCTCATGGATCGTGATGGCAATGGGAAGCTGGGCCTGGTGGAGTTCAACATCCTG +>SERBP1_K562_rep01_1718 +AGTACTTGCTTGGGGATGCGTTGCTGGTTCACCCTGTATCAGACTCTGGAGCCCATGGTGT +>SERBP1_K562_rep01_2914 +CTCTCCATGGCCAAGCCTGTGTACCATGCTATCACCAAGCACTCGCCCAAGAAGCCTGTCA +>SERBP1_K562_rep02_659 +AAAGACTTTGACACAGCCTTGAAGCATTACGACAAAGCCAAGGAGCTGGACCCCACTAACA +>SERBP1_K562_rep01_2089 +TTCTTTGCCTCCCAGGGCTGCGCCCAGAGTCCATTCCAGGCCGCGCCGGCGCCCCCGCCCA +>SERBP1_K562_rep01_1346 +CAACTTAGGTAACCCTCAGATGTCCCAGCAGACTTCATGTGCCTCCTTGGATTCTCCAGGA +>SERBP1_K562_rep01_2389 +AAGGTGGCATTGGTGAGGCTGTGTCCAGTGCAGTAGTGGGCGAGCCTGGCATCACTGTCAC +>SERBP1_K562_rep01_1078 +GGACCCTCGGGAGCAGCTGCGGGCGCTTACCTGCCCCCCCTGCAGCAGGTGTTCCAGGCAC +>SERBP1_K562_rep01_3211 +GTCCATCCTGCTGGAGGAGGTCAGCCCTGAGCTGGTGTGCAGCATGCTGCACCTCTGCTCT +>SERBP1_K562_rep02_166 +GGTGTAGACGCTGCTGGCCAGCCCGCCCCAGCCGAGGTTCTCGGCACCGCCTTGAGAGCTT +>SERBP1_K562_rep02_1331 +GCCGCTGCCGCTGCCGCTGTCGCTGTCGCCGCCGCCGCCGCCCGCCGCCGCCGCCGCCGCC +>SERBP1_K562_rep01_2447 +GATGTCTCTGTTGCTCCGCCGACCCCCTGGTCGTGAGGCCTATCCTGGTGATGTGTTCTAC +>SERBP1_K562_rep01_1027 +CATCCTCTCCCTCCACATCCTGGCACAGGCCTGCCTCCCCCTGCCCCAGCCCAGGGCCAGG +>SERBP1_K562_rep02_1279 +CCCCAGCGGCGGAGGCCCTCCCTGCTGTCTGAGTTCCAGCCCGGGAATGAACGGTCCCAGG +>SERBP1_K562_rep01_2685 +CAGAAGCTGGCAGCAGAGCGGGCCCGGGCGCCTGTGGTGCCCTACGGCGTGGACCTGCACT +>SERBP1_K562_rep02_620 +TCCCTGTCGCCACCGAGGTCGCACGCGTGAGACTTCTCCGCCGCCTCCGCCGCAGACGCCG +>SERBP1_K562_rep01_1791 +GCGGCCTCCGCTCGGCCCCCTCCCTCAGCTCCGGTGCGCGGCGGCCGACGACCCGCGCGGC +>SERBP1_K562_rep01_1117 +CTCCCCCAACTATGACCATGTGGTCCTGGGCGGTGGTCAGGAAGCCATGGATGTAACCACA +>SERBP1_K562_rep01_2729 +ACGAGCGCTGCACTAACGCAGGATCCGGCTGCCGAAGGTCCTCGCCAGCAGGATGAAGTTA +>SERBP1_K562_rep01_3199 +CCAACATGCCCAACCTGTACCCTGGGGCCCCTGGGGCTGGCTACCCACCAGTGCCCCCTGG +>SERBP1_K562_rep02_397 +CCTTTTCCGGTTGCGGCGCCGCGCGGTGAGGTTGTCTAGTCCACGCTCGGAGCCAT +>SERBP1_K562_rep02_1354 +AGCCCAGGCCCTGGCCATCCAGGCGGTGCTCCAGGCCGCGCAGCAGGCCGTCATGGGCACC +>SERBP1_K562_rep01_2163 +CGCATCCACGCGGTGAAGGACCACGGGCTCCAGGCCCCGCGGGCTGACCGCATCCTGTGCA +>SERBP1_K562_rep01_2209 +GGCGCATCATCCACCTGGTGCACCGCTTCAACGCCCACCACGGGGACACCAAGGTGGCGTA +>SERBP1_K562_rep01_854 +CAACGAGTCCTTTGGCTTCACCGCTGACCTGAGGTCCAACACGGGCGGCCAGGCGTTCCCC +>SERBP1_K562_rep01_77 +ACCTACATCATCAACATCAAGTTTGCTGACAAGCACGTGCCTGGAAGCCCCTTCACTGTGA +>SERBP1_K562_rep02_1404 +CGTACAATACCACTTCCGCTGTCACGGTAAAGTCCGCCATCAGAAGACTGAAGGAGTTGAA +>SERBP1_K562_rep01_712 +GACAGCGCCACAGAGGTCACAGGGCACCGCTGGCTGAAGGGGGGCGTGGTGCTGAAGGAGG +>SERBP1_K562_rep01_2518 +GTGCGGCGCTGAGGGACCCGGGCGAGCGCGCCGCGCACCGCCCCGCCGGCTCGCCTCCCTC +>SERBP1_K562_rep02_608 +GCACCCCTTTGGTTGGCCTTCCAACGGCTTCCCAGGGCCCCAGGGTCCATATTACTGTGGT +>SERBP1_K562_rep01_657 +AGTGGAGACAGAGCTTAAAATGTGGGACCCTCACAATGATCCCAATGCTCAGGGGGATGCC +>SERBP1_K562_rep01_1166 +GACCAGTGAGGCAGAATATGTATCGGGGATATAGACCACGATTCCGCAGGGGCCCTCCTCG +>SERBP1_K562_rep02_1497 +CTCTTTCCCTCGGAGCGGGCGGCGGCGTTGGCGGCTTGTGCAGCAATGGCCAAG +>SERBP1_K562_rep01_1946 +ATGACTTTGAGAAGAAGTTTAATGCGCTGAAGGTTCCCGTGCCAGAGGATAAATATACTGC +>SERBP1_K562_rep02_76 +CCGGTTCGCCGTCTGCGTCTCCCCCACGCCGCCTCGCCTGCCGCCGCGCTCGTCCCTCCGG +>SERBP1_K562_rep01_204 +CAAAACCCATAGTCAAGCCACAGACAAGCCCAGAATATGGCCAGGGGATCAATCCGATTAG +>SERBP1_K562_rep01_2128 +AACTCGACCTAGCCCCTCTCCGGAAAGGAGCAGCACAGGCCCAGAACCACCTGCTCCCACT +>SERBP1_K562_rep01_2335 +GACAAGGTGCCCAGTGTCTCCAGCTCTGCCCTCGTGTCTTCCTTGCACCTGCTGAAGTGCA +>SERBP1_K562_rep01_1136 +GCTCAGCCAGCTCCAGAAGCAGCTGGCAGCCAAGGAGGCGAAGCTTCGAGACCTGGAGGAC +>SERBP1_K562_rep01_2783 +GGCAAGCCCACCCACTTCACAGTAAATGCCAAAGCTGCTGGCAAAGGCAAGCTGGACGTCC +>SERBP1_K562_rep01_1319 +AGAGAGGTGTGCAGTGGCATGGAAGGGCCAGCGGGGTATCTGCGGCGGGCCAGTGTGGCCC +>SERBP1_K562_rep01_2182 +CAGATCCTGGAGTGGGCTCCATTTCTCCAGCTTCTCCAAAGATCTCCCTGGCCCCCACAGA +>SERBP1_K562_rep01_75 +CGTGTCCCGCTGCTGCTCCTGTGAGCGCCCGGCGAGTCCGTCCCGTCCACCGTCCGCAGCT +>SERBP1_K562_rep01_383 +CCACCCTATTCCCAGGGTCTTCCAAAACCGCTTCTCCACACAGTACCGCTGCTTCTCTGTG +>SERBP1_K562_rep02_1023 +CGCGCCCCGCGTCGGGTCCCATCCGGCCCATCGTGCGCTGCCCCACGGTTCGGTACCACAC +>SERBP1_K562_rep01_241 +TTCGCCTGCGTCGCTCCGGGAGCTGCCGACGGACGGAGCGCCCCCGCCCCCGCCCGGCCGC +>SERBP1_K562_rep02_709 +CTCCAAGGGCGGGCTTGTGCTCTGGTGCTTCCAGGGCGTTAGCGACTCATGCACCGGACCC +>SERBP1_K562_rep02_1521 +GACACCGTAACTATCCGCACTAGAAAGTTCATGACCAACCGACTACTTCAGAGGAAACAAA +>SERBP1_K562_rep01_1657 +CACGGCCGCATAGGCAAGCACCGGAAGCACCCCGGCGGCCGCGGTAATGCTGGTGGTCTGC +>SERBP1_K562_rep01_537 +AAACTTGGAGAAGGCCCAGGCGGAGCTGGTGGGGACAGCTGACGAGGCCACGCGGGCAGAG +>SERBP1_K562_rep01_1589 +ACCTCAGCCTCGGTGCTCGGGCCGCCCCGCCTCTGCCGGAAAGTCCGCGCCGCCGCTGCCG +>SERBP1_K562_rep01_2357 +CAGCGCCGCACCCGGAAGATGAGGCTCGCCGTGGGAGCCCTGCTGGTCTGCGCCGTCCTGG +>SERBP1_K562_rep02_851 +GTTTGCCGCCAGAACACAGGTAAGTGCCGTGTGTGGTT +>SERBP1_K562_rep01_2316 +CTCCTGCTGTATCGGCTCCGCTGGATACCGCACAACGACCACCACCACAGGGCTGCCCACA +>SERBP1_K562_rep01_482 +CTTCCTGAGAACCTTTATAATGACAGGATGTTTCGCATTAAGAGGGCACTGGACCTGAACT +>SERBP1_K562_rep01_424 +CGTGGTGAAGAGTGTGGCCTGGAACCCCAGCCCCGCTGTCTGCCTGGTGGCTGCAGCCGTG +>SERBP1_K562_rep02_946 +CGGTGCTGGTTTTTCGCTCGTCGACTGCGGCTCTTCCTCGGGCAGCGGAAGCGGCGCGGCG +>SERBP1_K562_rep02_299 +ACCAATGGCCAGCATGCTTTTTACCAGCTCATCCACCAAGGCACCAAGATGATACCCTGTG +>SERBP1_K562_rep02_910 +GCAACATCAGCTCACTGGAGGGGGCCCGGGGCCTCATTGCCGAGGCGGCGCAGCTTGGGCC +>SERBP1_K562_rep01_1047 +CCGAGCGATGGGCATCTCTCGGGACAACTGGCACAAGCGCCGCAAAACCGGGGGCAAGAGA +>SERBP1_K562_rep02_835 +GACTATCATTGATGCCCCAGGACACAGAGACTTTATCAAAAACATGATTACAGGGACATCT +>SERBP1_K562_rep01_2140 +GTCGCAGCGGCGGAGACCCCTGTGCGGTGCGGAGGGGGCGGCGGCCCCGACTCTGACCCGC +>SERBP1_K562_rep01_1040 +CCGCCGCCGCCGTTTCAGACGCAGACCCCACCGCAGAGTCTGCAGCAGCCCGCCCCGCCCG +>SERBP1_K562_rep01_1595 +AGAATGTTCTTGGTGAGAAGGGCCGGCGGATTCGGGAACTGACTGCTGTAGTTCAGAAGAG +>SERBP1_K562_rep02_1462 +GGGGAGCCAAAGGCATCCAGGCCAGGGCTCCTGTGGCAGCTGCCCCTGGCACCTGTGTTCC +>SERBP1_K562_rep01_3126 +GCGGAAGTTGGCCCTCTTTTCCGTGGCGCCTCGGAGGCGTTCAGCTGCTTCAAGATGAAGC +>SERBP1_K562_rep01_3060 +AAGTTAACCTCAATAATATCCGGAATATCCCCATCCCCACCCTCAAGGCATATGCAGAAGC +>SERBP1_K562_rep01_3300 +AAATGCAGAGAAATATGCTGAAGAAGACCGGCGAAAGAAGGAACGAGTTGAAGCAGTTAAT +>SERBP1_K562_rep02_1284 +TTGCCATTATGCAGACCCCTGCTGGGGAGCTGTATGACAAATCCATCATTCAGAGTGCCCA +>SERBP1_K562_rep01_2507 +TGGCAAGCATGTGGTGTTTGGCAAAGTTCTAGAGGGCATGGAGGTGGTGCGGAAGGTGGAG +>SERBP1_K562_rep01_22 +CACAGAGGAGCCAGTGAAGGTGCGGGAGGCTGGGGATGGTGTGTTCGAGTGCGAGTACTAC +>SERBP1_K562_rep01_1305 +CGAGCAGTGCTACTACGTCTTCGGGGATCTCTGCAGCAATCTCGCCACCCTGAACCTCAAC +>SERBP1_K562_rep02_1139 +CTGCGTATCAGTCCTCACCAGCAGGAGGACATGCACCAACTCCTCCAACTCCAGCGCCAAG +>SERBP1_K562_rep01_1878 +TGGAGTTCTCGGGCCGAGACGCCAGCGGCAAGCGTGTGATGGGACTGGTGCCTGCCAAGGG +>SERBP1_K562_rep01_25 +GCAGCCGAACAAAGGAGCAGGGGCGCCGCCGCAGGGACCCGCCACCCACCTCCCGGGGCCG
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.avg_profile Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,3610 @@ +CAPRIN1_pos_1 1 -1.379676 +CAPRIN1_pos_1 2 -1.655219 +CAPRIN1_pos_1 3 -1.263697 +CAPRIN1_pos_1 4 -0.881248 +CAPRIN1_pos_1 5 -0.380379 +CAPRIN1_pos_1 6 0.023880 +CAPRIN1_pos_1 7 0.322847 +CAPRIN1_pos_1 8 -0.050280 +CAPRIN1_pos_1 9 0.131240 +CAPRIN1_pos_1 10 -0.062237 +CAPRIN1_pos_1 11 -0.235974 +CAPRIN1_pos_1 12 -0.501274 +CAPRIN1_pos_1 13 -0.259123 +CAPRIN1_pos_1 14 -0.886778 +CAPRIN1_pos_1 15 -1.552642 +CAPRIN1_pos_1 16 -2.285816 +CAPRIN1_pos_1 17 -2.742947 +CAPRIN1_pos_1 18 -2.954979 +CAPRIN1_pos_1 19 -2.588990 +CAPRIN1_pos_1 20 -2.911601 +CAPRIN1_pos_1 21 -2.434019 +CAPRIN1_pos_1 22 -2.158966 +CAPRIN1_pos_1 23 -1.646564 +CAPRIN1_pos_1 24 -1.663726 +CAPRIN1_pos_1 25 -1.071446 +CAPRIN1_pos_1 26 -0.910116 +CAPRIN1_pos_1 27 -0.488377 +CAPRIN1_pos_1 28 -0.197663 +CAPRIN1_pos_1 29 -0.563750 +CAPRIN1_pos_1 30 -0.753612 +CAPRIN1_pos_1 31 -0.396876 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+CAPRIN1_pos_10 294 1.875287 +CAPRIN1_pos_10 295 1.758779 +CAPRIN1_pos_10 296 1.643259 +CAPRIN1_pos_10 297 1.207320 +CAPRIN1_pos_10 298 0.476141 +CAPRIN1_pos_10 299 0.396906 +CAPRIN1_pos_10 300 0.004435 +CAPRIN1_pos_10 301 -0.239439 +CAPRIN1_pos_10 302 0.013079 +CAPRIN1_pos_10 303 -0.129500 +CAPRIN1_pos_10 304 -0.404122 +CAPRIN1_pos_10 305 -0.600306 +CAPRIN1_pos_10 306 -0.552530 +CAPRIN1_pos_10 307 -0.542922 +CAPRIN1_pos_10 308 -0.366593 +CAPRIN1_pos_10 309 0.260696 +CAPRIN1_pos_10 310 0.368463 +CAPRIN1_pos_10 311 0.337125 +CAPRIN1_pos_10 312 0.546437 +CAPRIN1_pos_10 313 0.952587 +CAPRIN1_pos_10 314 1.125232 +CAPRIN1_pos_10 315 1.215464 +CAPRIN1_pos_10 316 1.456625 +CAPRIN1_pos_10 317 1.331600 +CAPRIN1_pos_10 318 1.317941 +CAPRIN1_pos_10 319 1.361951 +CAPRIN1_pos_10 320 1.133940 +CAPRIN1_pos_10 321 0.474719 +CAPRIN1_pos_10 322 0.273075 +CAPRIN1_pos_10 323 -0.180674 +CAPRIN1_pos_10 324 -0.400962 +CAPRIN1_pos_10 325 -0.996007 +CAPRIN1_pos_10 326 -0.675398 +CAPRIN1_pos_10 327 -0.699037 +CAPRIN1_pos_10 328 -1.140867 +CAPRIN1_pos_10 329 -1.166334 +CAPRIN1_pos_10 330 -0.921350 +CAPRIN1_pos_10 331 -1.305438 +CAPRIN1_pos_10 332 -1.190402 +CAPRIN1_pos_10 333 -0.929885 +CAPRIN1_pos_10 334 -0.503833 +CAPRIN1_pos_10 335 -0.429189 +CAPRIN1_pos_10 336 -0.090868 +CAPRIN1_pos_10 337 0.008666 +CAPRIN1_pos_10 338 -0.142423 +CAPRIN1_pos_10 339 0.273499 +CAPRIN1_pos_10 340 0.099133 +CAPRIN1_pos_10 341 0.338603 +CAPRIN1_pos_10 342 1.138634 +CAPRIN1_pos_10 343 1.672221 +CAPRIN1_pos_10 344 2.181895 +CAPRIN1_pos_10 345 2.305009 +CAPRIN1_pos_10 346 2.115692 +CAPRIN1_pos_10 347 2.493816 +CAPRIN1_pos_10 348 2.701728 +CAPRIN1_pos_10 349 2.941207 +CAPRIN1_pos_10 350 3.043532 +CAPRIN1_pos_10 351 3.314954 +CAPRIN1_pos_10 352 2.890958 +CAPRIN1_pos_10 353 2.266202 +CAPRIN1_pos_10 354 2.232321 +CAPRIN1_pos_10 355 1.949431 +CAPRIN1_pos_10 356 1.706469 +CAPRIN1_pos_10 357 1.872770 +CAPRIN1_pos_10 358 1.617284 +CAPRIN1_pos_10 359 1.286155 +CAPRIN1_pos_10 360 1.141618 +CAPRIN1_pos_10 361 0.797198
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.avg_profile.genomic_peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,100 @@ +chr4 53462672 53462674 CAPRIN1_pos_1,53462673 0.322847 - +chr4 53462670 53462671 CAPRIN1_pos_1,53462671 0.131240 - +chr4 53462630 53462632 CAPRIN1_pos_1,53462631 0.235923 - +chr4 53462610 53462612 CAPRIN1_pos_1,53462612 0.280927 - +chr4 53462406 53462408 CAPRIN1_pos_1,53462407 0.219724 - +chr4 53462329 53462330 CAPRIN1_pos_1,53462330 0.098335 - +chr4 53462326 53462327 CAPRIN1_pos_1,53462327 0.046050 - +chr3 196082839 196082841 CAPRIN1_pos_2,196082841 0.129521 - +chr3 196082803 196082805 CAPRIN1_pos_2,196082805 0.428493 - +chr3 196082801 196082802 CAPRIN1_pos_2,196082802 0.264655 - +chr3 196082794 196082796 CAPRIN1_pos_2,196082795 0.172488 - +chr3 196082728 196082736 CAPRIN1_pos_2,196082733 1.943816 - +chr3 196082711 196082712 CAPRIN1_pos_2,196082712 0.040976 - +chr3 196082704 196082710 CAPRIN1_pos_2,196082708 1.255144 - +chr3 196082665 196082675 CAPRIN1_pos_2,196082673 1.114239 - +chr3 196082571 196082575 CAPRIN1_pos_2,196082574 0.318163 - +chr3 196082493 196082495 CAPRIN1_pos_2,196082495 0.259428 - +chr18 659480 659499 CAPRIN1_pos_3,659492 1.592080 + +chr18 659503 659509 CAPRIN1_pos_3,659507 0.602029 + +chr18 659510 659514 CAPRIN1_pos_3,659512 0.299957 + +chr18 659520 659521 CAPRIN1_pos_3,659521 0.078966 + +chr18 659537 659562 CAPRIN1_pos_3,659558 1.790984 + +chr18 659576 659578 CAPRIN1_pos_3,659578 0.126206 + +chr18 659620 659622 CAPRIN1_pos_3,659621 0.143977 + +chr18 659652 659665 CAPRIN1_pos_3,659659 0.757031 + +chr18 659721 659727 CAPRIN1_pos_3,659725 0.911435 + +chr18 659757 659771 CAPRIN1_pos_3,659763 1.753765 + +chr18 659790 659800 CAPRIN1_pos_3,659795 1.424040 + +chr18 659808 659816 CAPRIN1_pos_3,659813 0.966312 + +chr18 659817 659818 CAPRIN1_pos_3,659818 0.024165 + +chr18 659822 659823 CAPRIN1_pos_3,659823 0.014006 + +chr18 659824 659826 CAPRIN1_pos_3,659825 0.263710 + +chr18 659839 659841 CAPRIN1_pos_3,659841 0.208979 + +chr14 45585296 45585297 CAPRIN1_pos_4,45585297 0.043554 - +chr14 45585250 45585252 CAPRIN1_pos_4,45585251 0.054336 - +chr14 45585171 45585177 CAPRIN1_pos_4,45585175 0.461447 - +chr14 45585042 45585043 CAPRIN1_pos_4,45585043 0.075030 - +chr14 45585037 45585040 CAPRIN1_pos_4,45585040 0.252767 - +chr14 45585035 45585036 CAPRIN1_pos_4,45585036 0.025491 - +chr14 45585024 45585033 CAPRIN1_pos_4,45585026 1.156303 - +chr19 58596235 58596415 CAPRIN1_pos_5,58596272 3.468620 - +chr19 58596229 58596230 CAPRIN1_pos_5,58596230 0.413088 - +chr19 58596185 58596228 CAPRIN1_pos_5,58596210 2.698865 - +chr19 58596054 58596182 CAPRIN1_pos_5,58596161 4.101235 - +chr4 109571760 109571776 CAPRIN1_pos_6,109571766 2.833152 + +chr4 109571778 109571814 CAPRIN1_pos_6,109571790 2.728851 + +chr4 109571827 109571833 CAPRIN1_pos_6,109571830 1.351761 + +chr4 109571849 109571884 CAPRIN1_pos_6,109571875 2.903897 + +chr4 109571888 109571904 CAPRIN1_pos_6,109571897 2.748033 + +chr4 109571940 109571950 CAPRIN1_pos_6,109571945 1.185336 + +chr4 109571957 109572019 CAPRIN1_pos_6,109572002 3.821982 + +chr4 109572020 109572021 CAPRIN1_pos_6,109572021 0.282644 + +chr4 109572022 109572027 CAPRIN1_pos_6,109572023 0.374493 + +chr4 109572030 109572047 CAPRIN1_pos_6,109572039 2.644698 + +chr4 109572076 109572081 CAPRIN1_pos_6,109572081 0.287939 + +chr4 109572092 109572098 CAPRIN1_pos_6,109572096 0.716058 + +chr8 42798383 42798389 CAPRIN1_pos_7,42798389 0.200465 + +chr8 42798465 42798466 CAPRIN1_pos_7,42798466 0.077973 + +chr8 42798520 42798531 CAPRIN1_pos_7,42798526 1.392449 + +chr8 42798578 42798586 CAPRIN1_pos_7,42798584 0.872296 + +chr8 42798668 42798676 CAPRIN1_pos_7,42798671 0.966690 + +chr8 42798678 42798679 CAPRIN1_pos_7,42798679 0.088335 + +chr8 42798697 42798709 CAPRIN1_pos_7,42798703 0.958345 + +chr1 11115017 11115041 CAPRIN1_pos_8,11115038 2.212693 - +chr1 11114998 11115015 CAPRIN1_pos_8,11115006 2.396456 - +chr1 11114958 11114992 CAPRIN1_pos_8,11114975 2.872385 - +chr1 11114956 11114957 CAPRIN1_pos_8,11114957 0.234594 - +chr1 11114952 11114955 CAPRIN1_pos_8,11114954 0.387833 - +chr1 11114936 11114950 CAPRIN1_pos_8,11114944 1.964977 - +chr1 11114810 11114925 CAPRIN1_pos_8,11114845 4.077125 - +chr1 11114760 11114801 CAPRIN1_pos_8,11114781 3.376777 - +chr1 11114716 11114738 CAPRIN1_pos_8,11114728 1.203373 - +chr1 11114710 11114715 CAPRIN1_pos_8,11114714 0.159993 - +chr1 11114697 11114709 CAPRIN1_pos_8,11114702 1.695643 - +chr1 117530511 117530531 CAPRIN1_pos_9,117530518 1.910565 + +chr1 117530536 117530548 CAPRIN1_pos_9,117530544 1.168142 + +chr1 117530561 117530571 CAPRIN1_pos_9,117530568 1.618727 + +chr1 117530599 117530605 CAPRIN1_pos_9,117530604 0.724791 + +chr1 117530617 117530619 CAPRIN1_pos_9,117530619 0.249549 + +chr1 117530620 117530621 CAPRIN1_pos_9,117530621 0.330394 + +chr1 117530630 117530642 CAPRIN1_pos_9,117530634 1.607942 + +chr1 117530651 117530654 CAPRIN1_pos_9,117530652 0.234019 + +chr1 117530668 117530669 CAPRIN1_pos_9,117530669 0.069593 + +chr1 117530684 117530687 CAPRIN1_pos_9,117530687 0.261641 + +chr1 117530707 117530708 CAPRIN1_pos_9,117530708 0.178237 + +chr1 117530740 117530747 CAPRIN1_pos_9,117530743 0.940394 + +chr1 117530794 117530802 CAPRIN1_pos_9,117530799 1.004641 + +chr1 117530857 117530862 CAPRIN1_pos_9,117530859 0.213619 + +chr22 43015872 43015879 CAPRIN1_pos_10,43015879 1.409827 - +chr22 43015846 43015864 CAPRIN1_pos_10,43015856 2.611975 - +chr22 43015789 43015844 CAPRIN1_pos_10,43015799 2.810422 - +chr22 43015727 43015780 CAPRIN1_pos_10,43015748 4.458784 - +chr22 43015656 43015723 CAPRIN1_pos_10,43015666 2.699599 - +chr22 43015606 43015649 CAPRIN1_pos_10,43015626 2.109173 - +chr22 43015601 43015605 CAPRIN1_pos_10,43015604 0.320538 - +chr22 43015579 43015599 CAPRIN1_pos_10,43015588 2.092991 - +chr22 43015577 43015578 CAPRIN1_pos_10,43015578 0.013079 - +chr22 43015557 43015571 CAPRIN1_pos_10,43015564 1.456625 - +chr22 43015542 43015543 CAPRIN1_pos_10,43015543 0.008666 - +chr22 43015518 43015541 CAPRIN1_pos_10,43015529 3.314954 -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.avg_profile.p50.genomic_peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,21 @@ +chr19 58596414 58596415 CAPRIN1_pos_5,58596415 2.940065 - +chr19 58596391 58596394 CAPRIN1_pos_5,58596393 2.897963 - +chr19 58596371 58596373 CAPRIN1_pos_5,58596373 2.854940 - +chr19 58596355 58596357 CAPRIN1_pos_5,58596356 2.979284 - +chr19 58596269 58596278 CAPRIN1_pos_5,58596272 3.468620 - +chr19 58596156 58596167 CAPRIN1_pos_5,58596161 4.101235 - +chr19 58596142 58596144 CAPRIN1_pos_5,58596143 2.884787 - +chr19 58596136 58596140 CAPRIN1_pos_5,58596137 3.165810 - +chr19 58596110 58596112 CAPRIN1_pos_5,58596112 2.917658 - +chr19 58596072 58596076 CAPRIN1_pos_5,58596074 3.078847 - +chr4 109571765 109571766 CAPRIN1_pos_6,109571766 2.833152 + +chr4 109571874 109571875 CAPRIN1_pos_6,109571875 2.903897 + +chr4 109571998 109572009 CAPRIN1_pos_6,109572002 3.821982 + +chr1 11114974 11114975 CAPRIN1_pos_8,11114975 2.872385 - +chr1 11114913 11114916 CAPRIN1_pos_8,11114916 3.124103 - +chr1 11114839 11114849 CAPRIN1_pos_8,11114845 4.077125 - +chr1 11114783 11114784 CAPRIN1_pos_8,11114784 3.139926 - +chr1 11114778 11114782 CAPRIN1_pos_8,11114781 3.376777 - +chr22 43015770 43015773 CAPRIN1_pos_10,43015772 3.033856 - +chr22 43015739 43015756 CAPRIN1_pos_10,43015748 4.458784 - +chr22 43015527 43015531 CAPRIN1_pos_10,43015529 3.314954 -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.avg_profile.p50.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,21 @@ +CAPRIN1_pos_5 0 1 CAPRIN1_pos_5,1 2.940065 + +CAPRIN1_pos_5 21 24 CAPRIN1_pos_5,23 2.897963 + +CAPRIN1_pos_5 42 44 CAPRIN1_pos_5,43 2.854940 + +CAPRIN1_pos_5 58 60 CAPRIN1_pos_5,60 2.979284 + +CAPRIN1_pos_5 137 146 CAPRIN1_pos_5,144 3.468620 + +CAPRIN1_pos_5 248 259 CAPRIN1_pos_5,255 4.101235 + +CAPRIN1_pos_5 271 273 CAPRIN1_pos_5,273 2.884787 + +CAPRIN1_pos_5 275 279 CAPRIN1_pos_5,279 3.165810 + +CAPRIN1_pos_5 303 305 CAPRIN1_pos_5,304 2.917658 + +CAPRIN1_pos_5 339 343 CAPRIN1_pos_5,342 3.078847 + +CAPRIN1_pos_6 5 6 CAPRIN1_pos_6,6 2.833152 + +CAPRIN1_pos_6 114 115 CAPRIN1_pos_6,115 2.903897 + +CAPRIN1_pos_6 238 249 CAPRIN1_pos_6,242 3.821982 + +CAPRIN1_pos_8 66 67 CAPRIN1_pos_8,67 2.872385 + +CAPRIN1_pos_8 125 128 CAPRIN1_pos_8,126 3.124103 + +CAPRIN1_pos_8 192 202 CAPRIN1_pos_8,197 4.077125 + +CAPRIN1_pos_8 257 258 CAPRIN1_pos_8,258 3.139926 + +CAPRIN1_pos_8 259 263 CAPRIN1_pos_8,261 3.376777 + +CAPRIN1_pos_10 106 109 CAPRIN1_pos_10,108 3.033856 + +CAPRIN1_pos_10 123 140 CAPRIN1_pos_10,132 4.458784 + +CAPRIN1_pos_10 348 352 CAPRIN1_pos_10,351 3.314954 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.avg_profile.peaks.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,100 @@ +CAPRIN1_pos_1 5 7 CAPRIN1_pos_1,7 0.322847 + +CAPRIN1_pos_1 8 9 CAPRIN1_pos_1,9 0.131240 + +CAPRIN1_pos_1 47 49 CAPRIN1_pos_1,49 0.235923 + +CAPRIN1_pos_1 67 69 CAPRIN1_pos_1,68 0.280927 + +CAPRIN1_pos_1 271 273 CAPRIN1_pos_1,273 0.219724 + +CAPRIN1_pos_1 349 350 CAPRIN1_pos_1,350 0.098335 + +CAPRIN1_pos_1 352 353 CAPRIN1_pos_1,353 0.046050 + +CAPRIN1_pos_2 0 2 CAPRIN1_pos_2,1 0.129521 + +CAPRIN1_pos_2 36 38 CAPRIN1_pos_2,37 0.428493 + +CAPRIN1_pos_2 39 40 CAPRIN1_pos_2,40 0.264655 + +CAPRIN1_pos_2 45 47 CAPRIN1_pos_2,47 0.172488 + +CAPRIN1_pos_2 105 113 CAPRIN1_pos_2,109 1.943816 + +CAPRIN1_pos_2 129 130 CAPRIN1_pos_2,130 0.040976 + +CAPRIN1_pos_2 131 137 CAPRIN1_pos_2,134 1.255144 + +CAPRIN1_pos_2 166 176 CAPRIN1_pos_2,169 1.114239 + +CAPRIN1_pos_2 266 270 CAPRIN1_pos_2,268 0.318163 + +CAPRIN1_pos_2 346 348 CAPRIN1_pos_2,347 0.259428 + +CAPRIN1_pos_3 0 19 CAPRIN1_pos_3,12 1.592080 + +CAPRIN1_pos_3 23 29 CAPRIN1_pos_3,27 0.602029 + +CAPRIN1_pos_3 30 34 CAPRIN1_pos_3,32 0.299957 + +CAPRIN1_pos_3 40 41 CAPRIN1_pos_3,41 0.078966 + +CAPRIN1_pos_3 57 82 CAPRIN1_pos_3,78 1.790984 + +CAPRIN1_pos_3 96 98 CAPRIN1_pos_3,98 0.126206 + +CAPRIN1_pos_3 140 142 CAPRIN1_pos_3,141 0.143977 + +CAPRIN1_pos_3 172 185 CAPRIN1_pos_3,179 0.757031 + +CAPRIN1_pos_3 241 247 CAPRIN1_pos_3,245 0.911435 + +CAPRIN1_pos_3 277 291 CAPRIN1_pos_3,283 1.753765 + +CAPRIN1_pos_3 310 320 CAPRIN1_pos_3,315 1.424040 + +CAPRIN1_pos_3 328 336 CAPRIN1_pos_3,333 0.966312 + +CAPRIN1_pos_3 337 338 CAPRIN1_pos_3,338 0.024165 + +CAPRIN1_pos_3 342 343 CAPRIN1_pos_3,343 0.014006 + +CAPRIN1_pos_3 344 346 CAPRIN1_pos_3,345 0.263710 + +CAPRIN1_pos_3 359 361 CAPRIN1_pos_3,361 0.208979 + +CAPRIN1_pos_4 88 89 CAPRIN1_pos_4,89 0.043554 + +CAPRIN1_pos_4 133 135 CAPRIN1_pos_4,135 0.054336 + +CAPRIN1_pos_4 208 214 CAPRIN1_pos_4,211 0.461447 + +CAPRIN1_pos_4 342 343 CAPRIN1_pos_4,343 0.075030 + +CAPRIN1_pos_4 345 348 CAPRIN1_pos_4,346 0.252767 + +CAPRIN1_pos_4 349 350 CAPRIN1_pos_4,350 0.025491 + +CAPRIN1_pos_4 352 361 CAPRIN1_pos_4,360 1.156303 + +CAPRIN1_pos_5 0 180 CAPRIN1_pos_5,144 3.468620 + +CAPRIN1_pos_5 185 186 CAPRIN1_pos_5,186 0.413088 + +CAPRIN1_pos_5 187 230 CAPRIN1_pos_5,206 2.698865 + +CAPRIN1_pos_5 233 361 CAPRIN1_pos_5,255 4.101235 + +CAPRIN1_pos_6 0 16 CAPRIN1_pos_6,6 2.833152 + +CAPRIN1_pos_6 18 54 CAPRIN1_pos_6,30 2.728851 + +CAPRIN1_pos_6 67 73 CAPRIN1_pos_6,70 1.351761 + +CAPRIN1_pos_6 89 124 CAPRIN1_pos_6,115 2.903897 + +CAPRIN1_pos_6 128 144 CAPRIN1_pos_6,137 2.748033 + +CAPRIN1_pos_6 180 190 CAPRIN1_pos_6,185 1.185336 + +CAPRIN1_pos_6 197 259 CAPRIN1_pos_6,242 3.821982 + +CAPRIN1_pos_6 260 261 CAPRIN1_pos_6,261 0.282644 + +CAPRIN1_pos_6 262 267 CAPRIN1_pos_6,263 0.374493 + +CAPRIN1_pos_6 270 287 CAPRIN1_pos_6,279 2.644698 + +CAPRIN1_pos_6 316 321 CAPRIN1_pos_6,321 0.287939 + +CAPRIN1_pos_6 332 338 CAPRIN1_pos_6,336 0.716058 + +CAPRIN1_pos_7 26 32 CAPRIN1_pos_7,32 0.200465 + +CAPRIN1_pos_7 108 109 CAPRIN1_pos_7,109 0.077973 + +CAPRIN1_pos_7 163 174 CAPRIN1_pos_7,169 1.392449 + +CAPRIN1_pos_7 221 229 CAPRIN1_pos_7,227 0.872296 + +CAPRIN1_pos_7 311 319 CAPRIN1_pos_7,314 0.966690 + +CAPRIN1_pos_7 321 322 CAPRIN1_pos_7,322 0.088335 + +CAPRIN1_pos_7 340 352 CAPRIN1_pos_7,346 0.958345 + +CAPRIN1_pos_8 0 24 CAPRIN1_pos_8,4 2.212693 + +CAPRIN1_pos_8 26 43 CAPRIN1_pos_8,36 2.396456 + +CAPRIN1_pos_8 49 83 CAPRIN1_pos_8,67 2.872385 + +CAPRIN1_pos_8 84 85 CAPRIN1_pos_8,85 0.234594 + +CAPRIN1_pos_8 86 89 CAPRIN1_pos_8,88 0.387833 + +CAPRIN1_pos_8 91 105 CAPRIN1_pos_8,98 1.964977 + +CAPRIN1_pos_8 116 231 CAPRIN1_pos_8,197 4.077125 + +CAPRIN1_pos_8 240 281 CAPRIN1_pos_8,261 3.376777 + +CAPRIN1_pos_8 303 325 CAPRIN1_pos_8,314 1.203373 + +CAPRIN1_pos_8 326 331 CAPRIN1_pos_8,328 0.159993 + +CAPRIN1_pos_8 332 344 CAPRIN1_pos_8,340 1.695643 + +CAPRIN1_pos_9 9 29 CAPRIN1_pos_9,16 1.910565 + +CAPRIN1_pos_9 34 46 CAPRIN1_pos_9,42 1.168142 + +CAPRIN1_pos_9 59 69 CAPRIN1_pos_9,66 1.618727 + +CAPRIN1_pos_9 97 103 CAPRIN1_pos_9,102 0.724791 + +CAPRIN1_pos_9 115 117 CAPRIN1_pos_9,117 0.249549 + +CAPRIN1_pos_9 118 119 CAPRIN1_pos_9,119 0.330394 + +CAPRIN1_pos_9 128 140 CAPRIN1_pos_9,132 1.607942 + +CAPRIN1_pos_9 149 152 CAPRIN1_pos_9,150 0.234019 + +CAPRIN1_pos_9 166 167 CAPRIN1_pos_9,167 0.069593 + +CAPRIN1_pos_9 182 185 CAPRIN1_pos_9,185 0.261641 + +CAPRIN1_pos_9 205 206 CAPRIN1_pos_9,206 0.178237 + +CAPRIN1_pos_9 238 245 CAPRIN1_pos_9,241 0.940394 + +CAPRIN1_pos_9 292 300 CAPRIN1_pos_9,297 1.004641 + +CAPRIN1_pos_9 355 360 CAPRIN1_pos_9,357 0.213619 + +CAPRIN1_pos_10 0 7 CAPRIN1_pos_10,1 1.409827 + +CAPRIN1_pos_10 15 33 CAPRIN1_pos_10,24 2.611975 + +CAPRIN1_pos_10 35 90 CAPRIN1_pos_10,81 2.810422 + +CAPRIN1_pos_10 99 152 CAPRIN1_pos_10,132 4.458784 + +CAPRIN1_pos_10 156 223 CAPRIN1_pos_10,214 2.699599 + +CAPRIN1_pos_10 230 273 CAPRIN1_pos_10,254 2.109173 + +CAPRIN1_pos_10 274 278 CAPRIN1_pos_10,276 0.320538 + +CAPRIN1_pos_10 280 300 CAPRIN1_pos_10,292 2.092991 + +CAPRIN1_pos_10 301 302 CAPRIN1_pos_10,302 0.013079 + +CAPRIN1_pos_10 308 322 CAPRIN1_pos_10,316 1.456625 + +CAPRIN1_pos_10 336 337 CAPRIN1_pos_10,337 0.008666 + +CAPRIN1_pos_10 338 361 CAPRIN1_pos_10,351 3.314954 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.bed Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,10 @@ +chr4 53462318 53462679 CAPRIN1_pos_1 0 - +chr3 196082480 196082841 CAPRIN1_pos_2 0 - +chr18 659480 659841 CAPRIN1_pos_3 0 + +chr14 45585024 45585385 CAPRIN1_pos_4 0 - +chr19 58596054 58596415 CAPRIN1_pos_5 0 - +chr4 109571760 109572121 CAPRIN1_pos_6 0 + +chr8 42798357 42798718 CAPRIN1_pos_7 0 + +chr1 11114680 11115041 CAPRIN1_pos_8 0 - +chr1 117530502 117530863 CAPRIN1_pos_9 0 + +chr22 43015518 43015879 CAPRIN1_pos_10 0 -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.fa Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,20 @@ +>CAPRIN1_pos_1 +ACAAAATGGCGCTGTTTCTTTGGCTCAGACTCCTAGAATGCTTGACAAGACAGAATTTTTTTGGAAGAACCTCATCTCACTATAGTTACTTTTTTCACTTTTGTTATATATGTATTTATTAGAGCATTTGAATATTGGTACCTTTAAAAGGGTCATTTGGTGTTTTGCTGTTGAGCTGGTTTTTGAGTCATAGATCTTGGCTTCCTTTAGAAGCCACTTAACTTCCATACACTATAATAAACTGTGAACATATTTTTGTTACCTAATGCATCCACTGATGAACATGCAAACTTTGGGCATAATGTGAACTAAAATTGAAATGGAAAATGTTAGTGGCCATTTTGCAACAATGAAGAGGATA +>CAPRIN1_pos_2 +GAGACAGTTTTCCTTATTACTCTGTATTGATCCTGCTAGTCCAAGAATGGACATGAAGTGAACCTATCGTGGTGACTGGGATAGGAAGGTGCTTGCTATTTTTGCCAGCACAGCATATTAGTTCCTTTGGAGCCCTCCATTGTCTGAGTCTGCAGTGATCTGTAGGAAGGCAGCTGGTCAATAATCATGTAGTACAATGGCTTGGAATTGTAACCACTATGGTTATTGATTGTCCTGTGTTGTTTCAGGCATACTTAGGTATGTCCCTGGGGAAAAAGAAAACCATTCAGCTGAGAGTTGCTAACCATGTTCTTTTGGTTAGAAATAATGGTTCATTTTTTGCCCCTGGTTGGAATAGTCT +>CAPRIN1_pos_3 +GCCTGGGAGCTCCACCGTGATCTCTGGCCCACTTTGCGGGAGTCTAGGCTTTCTGGATGCTCCAGGGCCTCACGTCCCAGGGCAGTTTTCTTCCCTGAAGAAAGTTGGATGGCATGATCTGTCTTCCCATCTTGAAACCGTATGGCAAATTGTTTTTCAGATGAATTCCCTCTGCTGACAACCAAACGTGTGTTCTGGAAGGGTGTTTTGGAGGAGTTGCTGTGGTTTATCAAGGTAAAGAAGTCGCTGCTATTAGAAGTCAGTAGTCTGTTCTCAACACAGCAGCCAGTGAGATCCTTTCAAAACTCAAAGCAGCCAGGTGTGGTGGCTCACGCCTGTAATCCCACCACTTTGGGAGGCT +>CAPRIN1_pos_4 +GCTCTAAGGATATTAGCAACAATGATAAAACTTGGCCTTGAAGAAATTTACACAACTAGTTAGAACTTGTTACTATTGTAAAGGAAGAGTCAACTGGAAAATTCAAGGAGTTAATAAAATTTGTTTACTTGGTCCCAGCTTTTGAGAGATAAATCCCTTATGAATCCCTGGTCTAAAATACTTTCCTACAGCTGTGTAAAATACTGGTCAAGGAGAACTTTTTCCTTTTACCTCATGTTGTAAACTTAAGTGGCTCAATAAAAATTGATCCACTGTCTTGATCTGACTGTGATTTGTTTGGTGTTAATATATTATTGTTCTGATTAGGGAATTGGAACTAAGGACCTCATCAAACCAGGGA +>CAPRIN1_pos_5 +CAGCGCAGGGCTGGAGGCCGGGCAGGGCCCTGGGGCTGACGAGCCGGGCTTGTCCCGCGGGAAGCCCTATGCCTGCGGCGAGTGCGGGGAGGCCTTCGCGTGGCTCTCGCACCTGATGGAGCACCACAGCAGCCATGGCGGCCGGAAGCGCTACGCCTGTCAGGGCTGCTGGAAGACCTTCCACTTCAGCCTGGCCCTAGCCGAGCACCAGAAGACCCACGAGAAGGAGAAAAGCTACGCGCTGGGGGGCGCCCGGGGCCCCCAACCGTCCACCCGCGAAGCCCAGGCGGGGGCTAGGGCGGGCGGTCCCCCAGAGAGCGTGGAGGGCGAGGCTCCCCCCGCACCCCCAGAGGCGCAGAGG +>CAPRIN1_pos_6 +CCGGGAGGCGCGTGGGGCTTGAGGCCGAGAACGGCCCTTGCTGCCACCAACATGGAGACTTTGTACCGTGTCCCGTTCTTAGTGCTCGAATGTCCCAACCTGAAGCTGAAGAAGCCGCCCTGGTTGCACATGCCGTCGGCCATGACTGTGTATGCTCTGGTGGTGGTGTCTTACTTCCTCATCACCGGAGGTAACTCGGGCTGTCGGGCCCGAGAGGCTGAGGAGCGGAGAACTGACCCGCCCCGGGAGGCGCGTCTGTTCCGCTGACTCTCAGCCCCGGGGGAAGCATAGCTCTGCTTTGGATCTTTTCTGAGGGTGGAGGGGAGTTCTGGGGTCCGAAGTGTTAACGTCCAAGTTTATT +>CAPRIN1_pos_7 +GGCAATGAGTTTCTGGTAATAACAAACCTCGATCAAGTTTTTTTTTTTTTTGGTCATATAAATGTAAATGCAATTATAATCCTTTTATCTCCATTCAGATTTTAGGACAGCAAATTAATGACTTTACCCTTCCTGATGTGAACCTTATTGGGGAGCATTCTGATGCAGCAGAGCTTGGAAGGATGCTTCAGCTCATCTTAGGCTGTGCTGTGAACTGTGAACAGAAGCAAGGTAATTTGTTTCAAGTTAGTGTTTGCATTTAAAATAATGAAGGAAAGTAGTGTATATTTTATATTTTATATATAAATCACCAGTACCAACAGTAACATCTGTTTAAGGTCACCCCCAAAGAATGCCATTT +>CAPRIN1_pos_8 +TGCTGCCCGAGTTTGCCCGCAAGGTGGGTGGCCTGCGGGGCTGGGTGGTGGGACCCAGGGACCCAGAGCGCCCTCCTGACTGGCCTCATGTCCCTCCAGGCCCTGAATGATGTGAGCTGAGCCCAGGCGCCACCACTGATGCCACCCAGGACCTCGGACCTTGGAGCCTGCGGGGTGCCTCGGCCCCTCCAGCCCCGGGCCGGACCTCCTGCTGGCTCTCGCCCACCAACCAAGTGTTACAAGCCCCAGAATGCTGCCCGGCCTGCCCTGCTGGGCGGACTGTCTGTGTGTCTGTCTCTCTGGCGTTCCACCTCCAAGCCTATACCAGCTGTGTACAGCGCCATCTCTCTGCCTTCTGTTG +>CAPRIN1_pos_9 +TATTCTTACGCAGCTGGGGCCAGGAGGGTCAGAGTGGTGCCAGGTGCAAGTTAGGCTAAAGAAGCCACCACTATTCCTCTCTCTTGCCCATTGTGGGGGGCAAAGGCATTGGTCACCAAGAGTCTTGCAGGGGGACCCACAGATATGCCATGTCCTTCACACGTGCTTGGGCTCCTTAACCTGAAGGCAAATTGCTACTTGCAAGACTGACTGACTTCAAGGAATCAGAAATTACCTAGAAGCACCATGTTTTTTCTATGACCTTTTCAGTCCTTCAGGTCATTTTAAGGTCCACTGCAGGGGGTTAGTGAGAAAGGGTATACTTTGTGGTATGTTTTGCTTTCCTAATAGGGACATGAAG +>CAPRIN1_pos_10 +CGCTGGTGCTGATGTGTGGCCCCCCACCCATGATCCAGTACGCCTGCCTTCCCAACCTGGACCACGTGGGCCACCCCACGGAGCGCTGCTTCGTCTTCTGAGGGCCGGGCACGGTCACACGGCCACCCGCCCCGCGCACCCCACGCCCTGTTCACGCTCACCCAGTCACCTCCCCACATCGCACACTGGGGCCCCGGGTTCAGCCTGGCCTGCCCGTGCCCTGGTGAATCACCTGGCTGAGCAGTTCCCCTGGAGCCCCTTCGGGAGCAGGGCTGTGTCCCAGATGGGCCACGGCTGAGCCTTCAGAGTACGTCCTGCCTGGCACTTACTGGTCCTTACCAGAGACGCCCAGCCCCATCCC
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.p50.predictions Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,3 @@ +CAPRIN1_pos_5 1 1.47084 +CAPRIN1_pos_8 1 0.79418 +CAPRIN1_pos_10 1 0.959388
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/test_predict.predictions Wed Jan 22 10:14:41 2020 -0500 @@ -0,0 +1,10 @@ +CAPRIN1_pos_1 -1 -1.61295 +CAPRIN1_pos_2 -1 -1.16685 +CAPRIN1_pos_3 -1 -0.565276 +CAPRIN1_pos_4 -1 -1.53879 +CAPRIN1_pos_5 1 1.47084 +CAPRIN1_pos_6 1 0.393163 +CAPRIN1_pos_7 -1 -1.43986 +CAPRIN1_pos_8 1 0.79418 +CAPRIN1_pos_9 -1 -0.74858 +CAPRIN1_pos_10 1 0.959388