Mercurial > repos > galaxyp > peptide_genomic_coordinate
changeset 0:5f49ffce52cb draft
planemo upload commit be7e9677908b7864ef0b965a1e219a1840eeb2ec
| author | galaxyp |
|---|---|
| date | Wed, 03 Apr 2019 04:04:18 -0400 |
| parents | |
| children | cb0378d2d487 |
| files | peptide_genomic_coordinate.py peptide_genomic_coordinate.xml test-data/peptides.tabular test-data/peptides_BED.bed test-data/test_genomic_mapping_sqlite.sqlite test-data/test_mz_to_sqlite.sqlite |
| diffstat | 6 files changed, 220 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/peptide_genomic_coordinate.py Wed Apr 03 04:04:18 2019 -0400 @@ -0,0 +1,154 @@ +#!/usr/bin/env python +# +# Author: Praveen Kumar +# University of Minnesota +# +# Get peptide's genomic coordinate from the protein's genomic mapping sqlite file (which is derived from the https://toolshed.g2.bx.psu.edu/view/galaxyp/translate_bed/038ecf54cbec) +# +# python peptideGenomicCoordinate.py <peptide_list> <mz_to_sqlite DB> <genomic mapping file DB> <output.bed> +# +import sys +import sqlite3 + + +def main(): + conn = sqlite3.connect(sys.argv[2]) + c = conn.cursor() + c.execute("DROP table if exists novel") + conn.commit() + c.execute("CREATE TABLE novel(peptide text)") + pepfile = open(sys.argv[1],"r") + + pep_seq = [] + for seq in pepfile.readlines(): + seq = seq.strip() + pep_seq.append(tuple([seq])) + + c.executemany("insert into novel(peptide) values(?)", pep_seq) + conn.commit() + + c.execute("SELECT distinct psm.sequence, ps.id, ps.sequence from db_sequence ps, psm_entries psm, novel n, proteins_by_peptide pbp where psm.sequence = n.peptide and pbp.peptide_ref = psm.id and pbp.id = ps.id") + rows = c.fetchall() + + conn1 = sqlite3.connect(sys.argv[3]) + c1 = conn1.cursor() + + outfh = open(sys.argv[4], "w") + + master_dict = {} + for each in rows: + peptide = each[0] + acc = each[1] + acc_seq = each[2] + + c1.execute("SELECT chrom,start,end,name,strand,cds_start,cds_end FROM feature_cds_map map WHERE map.name = '"+acc+"'") + coordinates = c1.fetchall() + + if len(coordinates) != 0: + pep_start = 0 + pep_end = 0 + flag = 0 + splice_flag = 0 + spliced_peptide = [] + for each_entry in coordinates: + chromosome = each_entry[0] + start = int(each_entry[1]) + end = int(each_entry[2]) + strand = each_entry[4] + cds_start = int(each_entry[5]) + cds_end = int(each_entry[6]) + pep_pos_start = (acc_seq.find(peptide)*3) + pep_pos_end = pep_pos_start + (len(peptide)*3) + if pep_pos_start >= cds_start and pep_pos_end <= cds_end: + if strand == "+": + pep_start = start + pep_pos_start - cds_start + pep_end = start + pep_pos_end - cds_start + pep_thick_start = 0 + pep_thick_end = len(peptide) + flag == 1 + else: + pep_end = end - pep_pos_start + cds_start + pep_start = end - pep_pos_end + cds_start + pep_thick_start = 0 + pep_thick_end = len(peptide) + flag == 1 + spliced_peptide = [] + splice_flag = 0 + else: + if flag == 0: + if strand == "+": + if pep_pos_start >= cds_start and pep_pos_start <= cds_end and pep_pos_end > cds_end: + pep_start = start + pep_pos_start - cds_start + pep_end = end + pep_thick_start = 0 + pep_thick_end = (pep_end-pep_start) + spliced_peptide.append([pep_start,pep_end,pep_thick_start,pep_thick_end]) + splice_flag = splice_flag + 1 + if splice_flag == 2: + flag = 1 + elif pep_pos_end >= cds_start and pep_pos_end <= cds_end and pep_pos_start < cds_start: + pep_start = start + pep_end = start + pep_pos_end - cds_start + pep_thick_start = (len(peptide)*3)-(pep_end-pep_start) + pep_thick_end = (len(peptide)*3) + spliced_peptide.append([pep_start,pep_end,pep_thick_start,pep_thick_end]) + splice_flag = splice_flag + 1 + if splice_flag == 2: + flag = 1 + else: + pass + else: + if pep_pos_start >= cds_start and pep_pos_start <= cds_end and pep_pos_end >= cds_end: + pep_start = start + pep_end = end - pep_pos_start - cds_start + pep_thick_start = 0 + pep_thick_end = (pep_end-pep_start) + spliced_peptide.append([pep_start,pep_end,pep_thick_start,pep_thick_end]) + splice_flag = splice_flag + 1 + if splice_flag == 2: + flag = 1 + elif pep_pos_end >= cds_start and pep_pos_end <= cds_end and pep_pos_start <= cds_start: + pep_start = end - pep_pos_end + cds_start + pep_end = end + pep_thick_start = (len(peptide)*3)-(pep_end-pep_start) + pep_thick_end = (len(peptide)*3) + spliced_peptide.append([pep_start,pep_end,pep_thick_start,pep_thick_end]) + splice_flag = splice_flag + 1 + if splice_flag == 2: + flag = 1 + else: + pass + + if len(spliced_peptide) == 0: + if strand == "+": + bed_line = [chromosome, str(pep_start), str(pep_end), peptide, "255", strand, str(pep_start), str(pep_end), "0", "1", str(pep_end-pep_start), "0"] + else: + bed_line = [chromosome, str(pep_start), str(pep_end), peptide, "255", strand, str(pep_start), str(pep_end), "0", "1", str(pep_end-pep_start), "0"] + outfh.write("\t".join(bed_line)+"\n") + else: + if strand == "+": + pep_entry = spliced_peptide + pep_start = min([pep_entry[0][0], pep_entry[1][0]]) + pep_end = max([pep_entry[0][1], pep_entry[1][1]]) + blockSize = [str(min([pep_entry[0][3], pep_entry[1][3]])),str(max([pep_entry[0][3], pep_entry[1][3]])-min([pep_entry[0][3], pep_entry[1][3]]))] + blockStarts = ["0", str(pep_end-pep_start-(max([pep_entry[0][3], pep_entry[1][3]])-min([pep_entry[0][3], pep_entry[1][3]])))] + bed_line = [chromosome, str(pep_start), str(pep_end), peptide, "255", strand, str(pep_start), str(pep_end), "0", "2", ",".join(blockSize), ",".join(blockStarts)] + outfh.write("\t".join(bed_line)+"\n") + else: + pep_entry = spliced_peptide + pep_start = min([pep_entry[0][0], pep_entry[1][0]]) + pep_end = max([pep_entry[0][1], pep_entry[1][1]]) + blockSize = [str(min([pep_entry[0][3], pep_entry[1][3]])),str(max([pep_entry[0][3], pep_entry[1][3]])-min([pep_entry[0][3], pep_entry[1][3]]))] + blockStarts = ["0", str(pep_end-pep_start-(max([pep_entry[0][3], pep_entry[1][3]])-min([pep_entry[0][3], pep_entry[1][3]])))] + bed_line = [chromosome, str(pep_start), str(pep_end), peptide, "255", strand, str(pep_start), str(pep_end), "0", "2", ",".join(blockSize), ",".join(blockStarts)] + outfh.write("\t".join(bed_line)+"\n") + c.execute("DROP table novel") + conn.commit() + conn.close() + conn1.close() + outfh.close() + pepfile.close() + + return None +if __name__ == "__main__": + main()
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/peptide_genomic_coordinate.xml Wed Apr 03 04:04:18 2019 -0400 @@ -0,0 +1,58 @@ +<tool id="peptide_genomic_coordinate" name="Peptide Genomic Coodinate" version="0.1.1"> + <description>Get Peptide's genomic coordinate using mzsqlite DB and genomic mapping sqlite DB</description> + <requirements> + <requirement type="package" version="3.7.1">python</requirement> + </requirements> + <command detect_errors="aggressive"><![CDATA[ + python '$__tool_directory__/peptide_genomic_coordinate.py' + '$peptideinput' + '$mzsqlite' + '$mapping' + '$peptide_bed' + ]]></command> + <inputs> + <param type="data" name="peptideinput" format="tabular" label="Peptide List (without any header line)"/> + <param type="data" name="mzsqlite" format="sqlite" label="mz to sqlite (mzsqlite) file"/> + <param type="data" name="mapping" format="sqlite" label="genomic mapping sqlite file"/> + </inputs> + <outputs> + <data format="bed" name="peptide_bed" label="${tool.name} on ${on_string}"> + <actions> + <action name="column_names" type="metadata" default="chrom,chromStart,chromStop,name,score,strand,thickStart,thickEnd,itemRgb,blockCount,blockSizes,blockStarts"/> + </actions> + </data> + </outputs> + <tests> + <test> + <param name="peptideinput" value="peptides.tabular"/> + <param name="mzsqlite" value="test_mz_to_sqlite.sqlite"/> + <param name="mapping" value="test_genomic_mapping_sqlite.sqlite"/> + <output name="peptide_bed"> + <assert_contents> + <has_text text="115176449" /> + </assert_contents> + </output> + </test> + </tests> + <help><![CDATA[ + **Peptide Genomic Coodinate** + + Gets genomic coordinate of peptides based on the information in mzsqlite and genomic mapping sqlite files. This tool is useful in a proteogenomics workflow. + This program loads two sqlite databases (mzsqlite and genomic mapping sqlite files) and calculates the genomic coordinates of the peptides provided as input. This outputs bed file for peptides. + + Input: Peptide list file, mzsqlite sqlite DB file, and genomic mapping sqlite DB file + Output: Tabular BED file with all the columns + + + + ]]></help> + <citations> + <citation type="bibtex"> +@misc{peptidegenomiccoodinate, + author={Kumar, Praveen}, + year={2018}, + title={Peptide Genomic Coordinate} +} + </citation> + </citations> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/peptides.tabular Wed Apr 03 04:04:18 2019 -0400 @@ -0,0 +1,4 @@ +AVDPDSSAEASGLR +DGDLENPVLYSGAVK +DSGASGSILEASAAR +ELGSSDLTAR
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/peptides_BED.bed Wed Apr 03 04:04:18 2019 -0400 @@ -0,0 +1,4 @@ +chr11 115176449 115176491 AVDPDSSAEASGLR 255 + 115176449 115176491 0 1 42 0 +chr5 121445444 121445489 DGDLENPVLYSGAVK 255 - 121445444 121445489 0 1 45 0 +chr17 22866997 22867042 DSGASGSILEASAAR 255 - 22866997 22867042 0 1 45 0 +chr2 91155262 91155292 ELGSSDLTAR 255 - 91155262 91155292 0 1 30 0