Mercurial > repos > davidvanzessen > shm_csr
diff shm_csr.py @ 81:b6f9a640e098 draft
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author | davidvanzessen |
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date | Fri, 19 Feb 2021 15:10:54 +0000 |
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children | 729738462297 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/shm_csr.py Fri Feb 19 15:10:54 2021 +0000 @@ -0,0 +1,508 @@ +import argparse +import logging +import sys +import os +import re + +from collections import defaultdict + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--input", help="The '7_V-REGION-mutation-and-AA-change-table' and '10_V-REGION-mutation-hotspots' merged together, with an added 'best_match' annotation") + parser.add_argument("--genes", help="The genes available in the 'best_match' column") + parser.add_argument("--empty_region_filter", help="Where does the sequence start?", choices=['leader', 'FR1', 'CDR1', 'FR2']) + parser.add_argument("--output", help="Output file") + + args = parser.parse_args() + + infile = args.input + genes = str(args.genes).split(",") + empty_region_filter = args.empty_region_filter + outfile = args.output + + genedic = dict() + + mutationdic = dict() + mutationMatcher = re.compile("^(.)(\d+).(.),?[ ]?(.)?(\d+)?.?(.)?(.?.?.?.?.?)?") + mutationMatcher = re.compile("^([actg])(\d+).([actg]),?[ ]?([A-Z])?(\d+)?.?([A-Z])?(.*)?") + mutationMatcher = re.compile("^([actg])(\d+).([actg]),?[ ]?([A-Z])?(\d+)?[>]?([A-Z;])?(.*)?") + mutationMatcher = re.compile("^([nactg])(\d+).([nactg]),?[ ]?([A-Z])?(\d+)?[>]?([A-Z;])?(.*)?") + NAMatchResult = (None, None, None, None, None, None, '') + geneMatchers = {gene: re.compile("^" + gene + ".*") for gene in genes} + linecount = 0 + + IDIndex = 0 + best_matchIndex = 0 + fr1Index = 0 + cdr1Index = 0 + fr2Index = 0 + cdr2Index = 0 + fr3Index = 0 + first = True + IDlist = [] + mutationList = [] + mutationListByID = {} + cdr1LengthDic = {} + cdr2LengthDic = {} + + fr1LengthDict = {} + fr2LengthDict = {} + fr3LengthDict = {} + + cdr1LengthIndex = 0 + cdr2LengthIndex = 0 + + fr1SeqIndex = 0 + fr2SeqIndex = 0 + fr3SeqIndex = 0 + + tandem_sum_by_class = defaultdict(int) + expected_tandem_sum_by_class = defaultdict(float) + + with open(infile, 'ru') as i: + for line in i: + if first: + linesplt = line.split("\t") + IDIndex = linesplt.index("Sequence.ID") + best_matchIndex = linesplt.index("best_match") + fr1Index = linesplt.index("FR1.IMGT") + cdr1Index = linesplt.index("CDR1.IMGT") + fr2Index = linesplt.index("FR2.IMGT") + cdr2Index = linesplt.index("CDR2.IMGT") + fr3Index = linesplt.index("FR3.IMGT") + cdr1LengthIndex = linesplt.index("CDR1.IMGT.length") + cdr2LengthIndex = linesplt.index("CDR2.IMGT.length") + fr1SeqIndex = linesplt.index("FR1.IMGT.seq") + fr2SeqIndex = linesplt.index("FR2.IMGT.seq") + fr3SeqIndex = linesplt.index("FR3.IMGT.seq") + first = False + continue + linecount += 1 + linesplt = line.split("\t") + ID = linesplt[IDIndex] + genedic[ID] = linesplt[best_matchIndex] + + mutationdic[ID + "_FR1"] = [] + if len(linesplt[fr1Index]) > 5 and empty_region_filter == "leader": + mutationdic[ID + "_FR1"] = [mutationMatcher.match(x).groups() for x in linesplt[fr1Index].split("|") if x] + + mutationdic[ID + "_CDR1"] = [] + if len(linesplt[cdr1Index]) > 5 and empty_region_filter in ["leader", "FR1"]: + mutationdic[ID + "_CDR1"] = [mutationMatcher.match(x).groups() for x in linesplt[cdr1Index].split("|") if x] + + mutationdic[ID + "_FR2"] = [] + if len(linesplt[fr2Index]) > 5 and empty_region_filter in ["leader", "FR1", "CDR1"]: + mutationdic[ID + "_FR2"] = [mutationMatcher.match(x).groups() for x in linesplt[fr2Index].split("|") if x] + + mutationdic[ID + "_CDR2"] = [] + if len(linesplt[cdr2Index]) > 5: + mutationdic[ID + "_CDR2"] = [mutationMatcher.match(x).groups() for x in linesplt[cdr2Index].split("|") if x] + + mutationdic[ID + "_FR2-CDR2"] = mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] + + mutationdic[ID + "_FR3"] = [] + if len(linesplt[fr3Index]) > 5: + mutationdic[ID + "_FR3"] = [mutationMatcher.match(x).groups() for x in linesplt[fr3Index].split("|") if x] + + mutationList += mutationdic[ID + "_FR1"] + mutationdic[ID + "_CDR1"] + mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] + mutationdic[ID + "_FR3"] + mutationListByID[ID] = mutationdic[ID + "_FR1"] + mutationdic[ID + "_CDR1"] + mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] + mutationdic[ID + "_FR3"] + + try: + cdr1Length = int(linesplt[cdr1LengthIndex]) + except: + cdr1Length = 0 + + try: + cdr2Length = int(linesplt[cdr2LengthIndex]) + except: + cdr2Length = 0 + + #print linesplt[fr2SeqIndex] + fr1Length = len(linesplt[fr1SeqIndex]) if empty_region_filter == "leader" else 0 + fr2Length = len(linesplt[fr2SeqIndex]) if empty_region_filter in ["leader", "FR1", "CDR1"] else 0 + fr3Length = len(linesplt[fr3SeqIndex]) + + cdr1LengthDic[ID] = cdr1Length + cdr2LengthDic[ID] = cdr2Length + + fr1LengthDict[ID] = fr1Length + fr2LengthDict[ID] = fr2Length + fr3LengthDict[ID] = fr3Length + + IDlist += [ID] + print "len(mutationdic) =", len(mutationdic) + + with open(os.path.join(os.path.dirname(os.path.abspath(infile)), "mutationdict.txt"), 'w') as out_handle: + for ID, lst in mutationdic.iteritems(): + for mut in lst: + out_handle.write("{0}\t{1}\n".format(ID, "\t".join([str(x) for x in mut]))) + + #tandem mutation stuff + tandem_frequency = defaultdict(int) + mutation_frequency = defaultdict(int) + + mutations_by_id_dic = {} + first = True + mutation_by_id_file = os.path.join(os.path.dirname(outfile), "mutation_by_id.txt") + with open(mutation_by_id_file, 'r') as mutation_by_id: + for l in mutation_by_id: + if first: + first = False + continue + splt = l.split("\t") + mutations_by_id_dic[splt[0]] = int(splt[1]) + + tandem_file = os.path.join(os.path.dirname(outfile), "tandems_by_id.txt") + with open(tandem_file, 'w') as o: + highest_tandem_length = 0 + + o.write("Sequence.ID\tnumber_of_mutations\tnumber_of_tandems\tregion_length\texpected_tandems\tlongest_tandem\ttandems\n") + for ID in IDlist: + mutations = mutationListByID[ID] + if len(mutations) == 0: + continue + last_mut = max(mutations, key=lambda x: int(x[1])) + + last_mut_pos = int(last_mut[1]) + + mut_positions = [False] * (last_mut_pos + 1) + + for mutation in mutations: + frm, where, to, frmAA, whereAA, toAA, thing = mutation + where = int(where) + mut_positions[where] = True + + tandem_muts = [] + tandem_start = -1 + tandem_length = 0 + for i in range(len(mut_positions)): + if mut_positions[i]: + if tandem_start == -1: + tandem_start = i + tandem_length += 1 + #print "".join(["1" if x else "0" for x in mut_positions[:i+1]]) + else: + if tandem_length > 1: + tandem_muts.append((tandem_start, tandem_length)) + #print "{0}{1} {2}:{3}".format(" " * (i - tandem_length), "^" * tandem_length, tandem_start, tandem_length) + tandem_start = -1 + tandem_length = 0 + if tandem_length > 1: # if the sequence ends with a tandem mutation + tandem_muts.append((tandem_start, tandem_length)) + + if len(tandem_muts) > 0: + if highest_tandem_length < len(tandem_muts): + highest_tandem_length = len(tandem_muts) + + region_length = fr1LengthDict[ID] + cdr1LengthDic[ID] + fr2LengthDict[ID] + cdr2LengthDic[ID] + fr3LengthDict[ID] + longest_tandem = max(tandem_muts, key=lambda x: x[1]) if len(tandem_muts) else (0, 0) + num_mutations = mutations_by_id_dic[ID] # len(mutations) + f_num_mutations = float(num_mutations) + num_tandem_muts = len(tandem_muts) + expected_tandem_muts = f_num_mutations * (f_num_mutations - 1.0) / float(region_length) + o.write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\n".format(ID, + str(num_mutations), + str(num_tandem_muts), + str(region_length), + str(round(expected_tandem_muts, 2)), + str(longest_tandem[1]), + str(tandem_muts))) + gene = genedic[ID] + if gene.find("unmatched") == -1: + tandem_sum_by_class[gene] += num_tandem_muts + expected_tandem_sum_by_class[gene] += expected_tandem_muts + + tandem_sum_by_class["all"] += num_tandem_muts + expected_tandem_sum_by_class["all"] += expected_tandem_muts + + gene = gene[:3] + if gene in ["IGA", "IGG"]: + tandem_sum_by_class[gene] += num_tandem_muts + expected_tandem_sum_by_class[gene] += expected_tandem_muts + else: + tandem_sum_by_class["unmatched"] += num_tandem_muts + expected_tandem_sum_by_class["unmatched"] += expected_tandem_muts + + + for tandem_mut in tandem_muts: + tandem_frequency[str(tandem_mut[1])] += 1 + #print "\t".join([ID, str(len(tandem_muts)), str(longest_tandem[1]) , str(tandem_muts)]) + + tandem_freq_file = os.path.join(os.path.dirname(outfile), "tandem_frequency.txt") + with open(tandem_freq_file, 'w') as o: + for frq in sorted([int(x) for x in tandem_frequency.keys()]): + o.write("{0}\t{1}\n".format(frq, tandem_frequency[str(frq)])) + + tandem_row = [] + genes_extra = list(genes) + genes_extra.append("all") + for x, y, in zip([tandem_sum_by_class[x] for x in genes_extra], [expected_tandem_sum_by_class[x] for x in genes_extra]): + if y != 0: + tandem_row += [x, round(y, 2), round(x / y, 2)] + else: + tandem_row += [x, round(y, 2), 0] + + tandem_freq_file = os.path.join(os.path.dirname(outfile), "shm_overview_tandem_row.txt") + with open(tandem_freq_file, 'w') as o: + o.write("Tandems/Expected (ratio),{0}\n".format(",".join([str(x) for x in tandem_row]))) + + #print mutationList, linecount + + AALength = (int(max(mutationList, key=lambda i: int(i[4]) if i[4] and i[5] != ";" else 0)[4]) + 1) # [4] is the position of the AA mutation, None if silent + if AALength < 60: + AALength = 64 + + AA_mutation = [0] * AALength + AA_mutation_dic = {"IGA": AA_mutation[:], "IGG": AA_mutation[:], "IGM": AA_mutation[:], "IGE": AA_mutation[:], "unm": AA_mutation[:], "all": AA_mutation[:]} + AA_mutation_empty = AA_mutation[:] + + print "AALength:", AALength + aa_mutations_by_id_file = outfile[:outfile.rindex("/")] + "/aa_id_mutations.txt" + with open(aa_mutations_by_id_file, 'w') as o: + o.write("ID\tbest_match\t" + "\t".join([str(x) for x in range(1,AALength)]) + "\n") + for ID in mutationListByID.keys(): + AA_mutation_for_ID = AA_mutation_empty[:] + for mutation in mutationListByID[ID]: + if mutation[4] and mutation[5] != ";": + AA_mutation_position = int(mutation[4]) + try: + AA_mutation[AA_mutation_position] += 1 + AA_mutation_for_ID[AA_mutation_position] += 1 + except Exception as e: + print e + print mutation + sys.exit() + clss = genedic[ID][:3] + AA_mutation_dic[clss][AA_mutation_position] += 1 + o.write(ID + "\t" + genedic[ID] + "\t" + "\t".join([str(x) for x in AA_mutation_for_ID[1:]]) + "\n") + + + + #absent AA stuff + absentAACDR1Dic = defaultdict(list) + absentAACDR1Dic[5] = range(29,36) + absentAACDR1Dic[6] = range(29,35) + absentAACDR1Dic[7] = range(30,35) + absentAACDR1Dic[8] = range(30,34) + absentAACDR1Dic[9] = range(31,34) + absentAACDR1Dic[10] = range(31,33) + absentAACDR1Dic[11] = [32] + + absentAACDR2Dic = defaultdict(list) + absentAACDR2Dic[0] = range(55,65) + absentAACDR2Dic[1] = range(56,65) + absentAACDR2Dic[2] = range(56,64) + absentAACDR2Dic[3] = range(57,64) + absentAACDR2Dic[4] = range(57,63) + absentAACDR2Dic[5] = range(58,63) + absentAACDR2Dic[6] = range(58,62) + absentAACDR2Dic[7] = range(59,62) + absentAACDR2Dic[8] = range(59,61) + absentAACDR2Dic[9] = [60] + + absentAA = [len(IDlist)] * (AALength-1) + for k, cdr1Length in cdr1LengthDic.iteritems(): + for c in absentAACDR1Dic[cdr1Length]: + absentAA[c] -= 1 + + for k, cdr2Length in cdr2LengthDic.iteritems(): + for c in absentAACDR2Dic[cdr2Length]: + absentAA[c] -= 1 + + + aa_mutations_by_id_file = outfile[:outfile.rindex("/")] + "/absent_aa_id.txt" + with open(aa_mutations_by_id_file, 'w') as o: + o.write("ID\tcdr1length\tcdr2length\tbest_match\t" + "\t".join([str(x) for x in range(1,AALength)]) + "\n") + for ID in IDlist: + absentAAbyID = [1] * (AALength-1) + cdr1Length = cdr1LengthDic[ID] + for c in absentAACDR1Dic[cdr1Length]: + absentAAbyID[c] -= 1 + + cdr2Length = cdr2LengthDic[ID] + for c in absentAACDR2Dic[cdr2Length]: + absentAAbyID[c] -= 1 + o.write(ID + "\t" + str(cdr1Length) + "\t" + str(cdr2Length) + "\t" + genedic[ID] + "\t" + "\t".join([str(x) for x in absentAAbyID]) + "\n") + + if linecount == 0: + print "No data, exiting" + with open(outfile, 'w') as o: + o.write("RGYW (%)," + ("0,0,0\n" * len(genes))) + o.write("WRCY (%)," + ("0,0,0\n" * len(genes))) + o.write("WA (%)," + ("0,0,0\n" * len(genes))) + o.write("TW (%)," + ("0,0,0\n" * len(genes))) + import sys + + sys.exit() + + hotspotMatcher = re.compile("[actg]+,(\d+)-(\d+)\((.*)\)") + RGYWCount = {} + WRCYCount = {} + WACount = {} + TWCount = {} + + #IDIndex = 0 + ataIndex = 0 + tatIndex = 0 + aggctatIndex = 0 + atagcctIndex = 0 + first = True + with open(infile, 'ru') as i: + for line in i: + if first: + linesplt = line.split("\t") + ataIndex = linesplt.index("X.a.t.a") + tatIndex = linesplt.index("t.a.t.") + aggctatIndex = linesplt.index("X.a.g.g.c.t..a.t.") + atagcctIndex = linesplt.index("X.a.t..a.g.c.c.t.") + first = False + continue + linesplt = line.split("\t") + gene = linesplt[best_matchIndex] + ID = linesplt[IDIndex] + RGYW = [(int(x), int(y), z) for (x, y, z) in + [hotspotMatcher.match(x).groups() for x in linesplt[aggctatIndex].split("|") if x]] + WRCY = [(int(x), int(y), z) for (x, y, z) in + [hotspotMatcher.match(x).groups() for x in linesplt[atagcctIndex].split("|") if x]] + WA = [(int(x), int(y), z) for (x, y, z) in + [hotspotMatcher.match(x).groups() for x in linesplt[ataIndex].split("|") if x]] + TW = [(int(x), int(y), z) for (x, y, z) in + [hotspotMatcher.match(x).groups() for x in linesplt[tatIndex].split("|") if x]] + RGYWCount[ID], WRCYCount[ID], WACount[ID], TWCount[ID] = 0, 0, 0, 0 + + with open(os.path.join(os.path.dirname(os.path.abspath(infile)), "RGYW.txt"), 'a') as out_handle: + for hotspot in RGYW: + out_handle.write("{0}\t{1}\n".format(ID, "\t".join([str(x) for x in hotspot]))) + + mutationList = mutationdic[ID + "_FR1"] + mutationdic[ID + "_CDR1"] + mutationdic[ID + "_FR2"] + mutationdic[ID + "_CDR2"] + mutationdic[ID + "_FR3"] + for mutation in mutationList: + frm, where, to, AAfrm, AAwhere, AAto, junk = mutation + mutation_in_RGYW = any(((start <= int(where) <= end) for (start, end, region) in RGYW)) + mutation_in_WRCY = any(((start <= int(where) <= end) for (start, end, region) in WRCY)) + mutation_in_WA = any(((start <= int(where) <= end) for (start, end, region) in WA)) + mutation_in_TW = any(((start <= int(where) <= end) for (start, end, region) in TW)) + + in_how_many_motifs = sum([mutation_in_RGYW, mutation_in_WRCY, mutation_in_WA, mutation_in_TW]) + + if in_how_many_motifs > 0: + RGYWCount[ID] += (1.0 * int(mutation_in_RGYW)) / in_how_many_motifs + WRCYCount[ID] += (1.0 * int(mutation_in_WRCY)) / in_how_many_motifs + WACount[ID] += (1.0 * int(mutation_in_WA)) / in_how_many_motifs + TWCount[ID] += (1.0 * int(mutation_in_TW)) / in_how_many_motifs + + mutations_in_motifs_file = os.path.join(os.path.dirname(os.path.abspath(infile)), "mutation_in_motifs.txt") + if not os.path.exists(mutation_by_id_file): + with open(mutations_in_motifs_file, 'w') as out_handle: + out_handle.write("{0}\n".format("\t".join([ + "Sequence.ID", + "mutation_position", + "region", + "from_nt", + "to_nt", + "mutation_position_AA", + "from_AA", + "to_AA", + "motif", + "motif_start_nt", + "motif_end_nt", + "rest" + ]))) + + with open(mutations_in_motifs_file, 'a') as out_handle: + motif_dic = {"RGYW": RGYW, "WRCY": WRCY, "WA": WA, "TW": TW} + for mutation in mutationList: + frm, where, to, AAfrm, AAwhere, AAto, junk = mutation + for motif in motif_dic.keys(): + + for start, end, region in motif_dic[motif]: + if start <= int(where) <= end: + out_handle.write("{0}\n".format( + "\t".join([ + ID, + where, + region, + frm, + to, + str(AAwhere), + str(AAfrm), + str(AAto), + motif, + str(start), + str(end), + str(junk) + ]) + )) + + + + def mean(lst): + return (float(sum(lst)) / len(lst)) if len(lst) > 0 else 0.0 + + + def median(lst): + lst = sorted(lst) + l = len(lst) + if l == 0: + return 0 + if l == 1: + return lst[0] + + l = int(l / 2) + + if len(lst) % 2 == 0: + return float(lst[l] + lst[(l - 1)]) / 2.0 + else: + return lst[l] + + funcs = {"mean": mean, "median": median, "sum": sum} + + directory = outfile[:outfile.rfind("/") + 1] + value = 0 + valuedic = dict() + + for fname in funcs.keys(): + for gene in genes: + with open(directory + gene + "_" + fname + "_value.txt", 'r') as v: + valuedic[gene + "_" + fname] = float(v.readlines()[0].rstrip()) + with open(directory + "all_" + fname + "_value.txt", 'r') as v: + valuedic["total_" + fname] = float(v.readlines()[0].rstrip()) + + + def get_xyz(lst, gene, f, fname): + x = round(round(f(lst), 1)) + y = valuedic[gene + "_" + fname] + z = str(round(x / float(y) * 100, 1)) if y != 0 else "0" + return (str(x), str(y), z) + + dic = {"RGYW": RGYWCount, "WRCY": WRCYCount, "WA": WACount, "TW": TWCount} + arr = ["RGYW", "WRCY", "WA", "TW"] + + for fname in funcs.keys(): + func = funcs[fname] + foutfile = outfile[:outfile.rindex("/")] + "/hotspot_analysis_" + fname + ".txt" + with open(foutfile, 'w') as o: + for typ in arr: + o.write(typ + " (%)") + curr = dic[typ] + for gene in genes: + geneMatcher = geneMatchers[gene] + if valuedic[gene + "_" + fname] is 0: + o.write(",0,0,0") + else: + x, y, z = get_xyz([curr[x] for x in [y for y, z in genedic.iteritems() if geneMatcher.match(z)]], gene, func, fname) + o.write("," + x + "," + y + "," + z) + x, y, z = get_xyz([y for x, y in curr.iteritems() if not genedic[x].startswith("unmatched")], "total", func, fname) + #x, y, z = get_xyz([y for x, y in curr.iteritems()], "total", func, fname) + o.write("," + x + "," + y + "," + z + "\n") + + + # for testing + seq_motif_file = outfile[:outfile.rindex("/")] + "/motif_per_seq.txt" + with open(seq_motif_file, 'w') as o: + o.write("ID\tRGYW\tWRCY\tWA\tTW\n") + for ID in IDlist: + #o.write(ID + "\t" + str(round(RGYWCount[ID], 2)) + "\t" + str(round(WRCYCount[ID], 2)) + "\t" + str(round(WACount[ID], 2)) + "\t" + str(round(TWCount[ID], 2)) + "\n") + o.write(ID + "\t" + str(RGYWCount[ID]) + "\t" + str(WRCYCount[ID]) + "\t" + str(WACount[ID]) + "\t" + str(TWCount[ID]) + "\n") + +if __name__ == "__main__": + main()