Mercurial > repos > galaxyp > pep_pointer
comparison pep_pointer.py @ 4:3a3aff93ee9e draft default tip
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/pep_pointer commit 494bc6dd87b9a6e2af40cb32aa5d2ee6e9bfebfc
| author | galaxyp |
|---|---|
| date | Mon, 20 Jun 2022 13:59:17 +0000 |
| parents | a26f551d819b |
| children |
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| 3:a26f551d819b | 4:3a3aff93ee9e |
|---|---|
| 1 | 1 |
| 2 # | 2 # |
| 3 # Author: Praveen Kumar | 3 # Author: Praveen Kumar |
| 4 # Updated: April 6th, 2018 | 4 # Updated: April 6th, 2018 (updated to python3: May 2022) |
| 5 # | 5 # |
| 6 # | 6 # |
| 7 # | 7 # |
| 8 | 8 |
| 9 import re | 9 import re |
| 10 | 10 |
| 11 | 11 |
| 12 def main(): | 12 def main(): |
| 13 import sys | 13 import sys |
| 14 if len(sys.argv) == 4: | 14 if len(sys.argv) == 4: |
| 15 inputFile = sys.argv | 15 inputFile = sys.argv |
| 16 infh = open(inputFile[1], "r") | 16 infh = open(inputFile[1], "r") |
| 17 # infh = open("Mus_musculus.GRCm38.90.chr.gtf", "r") | 17 # infh = open("Mus_musculus.GRCm38.90.chr.gtf", "r") |
| 18 | 18 |
| 19 gtf = {} | 19 gtf = {} |
| 20 gtf_transcript = {} | 20 gtf_transcript = {} |
| 21 gtf_gene = {} | 21 gtf_gene = {} |
| 22 for each in infh.readlines(): | 22 for each in infh.readlines(): |
| 23 a = each.split("\t") | 23 a = each.split("\t") |
| 36 end = a[4].strip() | 36 end = a[4].strip() |
| 37 elif int(a[4].strip()) < int(a[3].strip()): | 37 elif int(a[4].strip()) < int(a[3].strip()): |
| 38 start = a[4].strip() | 38 start = a[4].strip() |
| 39 end = a[3].strip() | 39 end = a[3].strip() |
| 40 else: | 40 else: |
| 41 print "Please check the start end coordinates in the GTF file" | 41 print("Please check the start end coordinates in the GTF file") |
| 42 else: | 42 else: |
| 43 print "Please check the strand information in the GTF file. It should be '+' or '-'." | 43 print("Please check the strand information in the GTF file. It should be '+' or '-'.") |
| 44 if not gtf.has_key(strand): | 44 if strand not in gtf: |
| 45 gtf[strand] = {} | 45 gtf[strand] = {} |
| 46 if not gtf[strand].has_key(type): | 46 if type not in gtf[strand]: |
| 47 gtf[strand][type] = [] | 47 gtf[strand][type] = [] |
| 48 b = re.search("gene_id \"(.+?)\";", a[8].strip()) | 48 b = re.search("gene_id \"(.+?)\";", a[8].strip()) |
| 49 gene = b.group(1) | 49 gene = b.group(1) |
| 50 if type == "gene": | 50 if type == "gene": |
| 51 transcript = "" | 51 transcript = "" |
| 52 else: | 52 else: |
| 53 b = re.search("transcript_id \"(.+?)\";", a[8].strip()) | 53 b = re.search("transcript_id \"(.+?)\";", a[8].strip()) |
| 54 transcript = b.group(1) | 54 transcript = b.group(1) |
| 55 data = (chr, start, end, gene, transcript, strand, type) | 55 data = (chr, start, end, gene, transcript, strand, type) |
| 56 gtf[strand][type].append(data) | 56 gtf[strand][type].append(data) |
| 57 | 57 |
| 58 if type == "exon": | 58 if type == "exon": |
| 59 if gtf_transcript.has_key(chr+"#"+strand): | 59 if chr + "#" + strand in gtf_transcript: |
| 60 if gtf_transcript[chr+"#"+strand].has_key(transcript+"#"+gene): | 60 if transcript + "#" + gene in gtf_transcript[chr + "#" + strand]: |
| 61 gtf_transcript[chr+"#"+strand][transcript+"#"+gene][0].append(int(start)) | 61 gtf_transcript[chr + "#" + strand][transcript + "#" + gene][0].append(int(start)) |
| 62 gtf_transcript[chr+"#"+strand][transcript+"#"+gene][1].append(int(end)) | 62 gtf_transcript[chr + "#" + strand][transcript + "#" + gene][1].append(int(end)) |
| 63 else: | 63 else: |
| 64 gtf_transcript[chr+"#"+strand][transcript+"#"+gene] = [[],[]] | 64 gtf_transcript[chr + "#" + strand][transcript + "#" + gene] = [[], []] |
| 65 gtf_transcript[chr+"#"+strand][transcript+"#"+gene][0].append(int(start)) | 65 gtf_transcript[chr + "#" + strand][transcript + "#" + gene][0].append(int(start)) |
| 66 gtf_transcript[chr+"#"+strand][transcript+"#"+gene][1].append(int(end)) | 66 gtf_transcript[chr + "#" + strand][transcript + "#" + gene][1].append(int(end)) |
| 67 else: | 67 else: |
| 68 gtf_transcript[chr+"#"+strand] = {} | 68 gtf_transcript[chr + "#" + strand] = {} |
| 69 gtf_transcript[chr+"#"+strand][transcript+"#"+gene] = [[],[]] | 69 gtf_transcript[chr + "#" + strand][transcript + "#" + gene] = [[], []] |
| 70 gtf_transcript[chr+"#"+strand][transcript+"#"+gene][0].append(int(start)) | 70 gtf_transcript[chr + "#" + strand][transcript + "#" + gene][0].append(int(start)) |
| 71 gtf_transcript[chr+"#"+strand][transcript+"#"+gene][1].append(int(end)) | 71 gtf_transcript[chr + "#" + strand][transcript + "#" + gene][1].append(int(end)) |
| 72 | 72 |
| 73 if type == "gene": | 73 if type == "gene": |
| 74 if gtf_gene.has_key(chr+"#"+strand): | 74 if chr + "#" + strand in gtf_gene: |
| 75 gtf_gene[chr+"#"+strand][0].append(int(start)) | 75 gtf_gene[chr + "#" + strand][0].append(int(start)) |
| 76 gtf_gene[chr+"#"+strand][1].append(int(end)) | 76 gtf_gene[chr + "#" + strand][1].append(int(end)) |
| 77 gtf_gene[chr+"#"+strand][2].append(gene) | 77 gtf_gene[chr + "#" + strand][2].append(gene) |
| 78 else: | 78 else: |
| 79 gtf_gene[chr+"#"+strand] = [[0],[0],["no_gene"]] | 79 gtf_gene[chr + "#" + strand] = [[0], [0], ["no_gene"]] |
| 80 gtf_gene[chr+"#"+strand][0].append(int(start)) | 80 gtf_gene[chr + "#" + strand][0].append(int(start)) |
| 81 gtf_gene[chr+"#"+strand][1].append(int(end)) | 81 gtf_gene[chr + "#" + strand][1].append(int(end)) |
| 82 gtf_gene[chr+"#"+strand][2].append(gene) | 82 gtf_gene[chr + "#" + strand][2].append(gene) |
| 83 | 83 |
| 84 | |
| 85 | |
| 86 # "Starting Reading Intron . . ." | 84 # "Starting Reading Intron . . ." |
| 87 | 85 |
| 88 gtf["+"]["intron"] = [] | 86 gtf["+"]["intron"] = [] |
| 89 gtf["-"]["intron"] = [] | 87 gtf["-"]["intron"] = [] |
| 90 for chr_strand in gtf_transcript.keys(): | 88 for chr_strand in gtf_transcript.keys(): |
| 91 chr = chr_strand.split("#")[0] | 89 chr = chr_strand.split("#")[0] |
| 92 strand = chr_strand.split("#")[1] | 90 strand = chr_strand.split("#")[1] |
| 93 | 91 |
| 94 for transcript_gene in gtf_transcript[chr_strand].keys(): | 92 for transcript_gene in gtf_transcript[chr_strand].keys(): |
| 95 start_list = gtf_transcript[chr_strand][transcript_gene][0] | 93 start_list = gtf_transcript[chr_strand][transcript_gene][0] |
| 96 end_list = gtf_transcript[chr_strand][transcript_gene][1] | 94 end_list = gtf_transcript[chr_strand][transcript_gene][1] |
| 97 sorted_start_index = [i[0] for i in sorted(enumerate(start_list), key=lambda x:x[1])] | 95 sorted_start_index = [i[0] for i in sorted(enumerate(start_list), key=lambda x:x[1])] |
| 98 sorted_end_index = [i[0] for i in sorted(enumerate(end_list), key=lambda x:x[1])] | 96 sorted_end_index = [i[0] for i in sorted(enumerate(end_list), key=lambda x:x[1])] |
| 99 if sorted_start_index == sorted_end_index: | 97 if sorted_start_index == sorted_end_index: |
| 100 sorted_start = sorted(start_list) | 98 sorted_start = sorted(start_list) |
| 101 sorted_end = [end_list[i] for i in sorted_start_index] | 99 sorted_end = [end_list[i] for i in sorted_start_index] |
| 102 for x in range(len(sorted_start))[1:]: | 100 for x in range(len(sorted_start))[1:]: |
| 103 intron_start = sorted_end[x-1]+1 | 101 intron_start = sorted_end[x - 1] + 1 |
| 104 intron_end = sorted_start[x]-1 | 102 intron_end = sorted_start[x] - 1 |
| 105 transcript = transcript_gene.split("#")[0] | 103 transcript = transcript_gene.split("#")[0] |
| 106 gene = transcript_gene.split("#")[1] | 104 gene = transcript_gene.split("#")[1] |
| 107 data = (chr, str(intron_start), str(intron_end), gene, transcript, strand, "intron") | 105 data = (chr, str(intron_start), str(intron_end), gene, transcript, strand, "intron") |
| 108 gtf[strand]["intron"].append(data) | 106 gtf[strand]["intron"].append(data) |
| 109 | 107 |
| 110 | |
| 111 # "Starting Reading Intergenic . . ." | 108 # "Starting Reading Intergenic . . ." |
| 112 | 109 |
| 113 gtf["+"]["intergenic"] = [] | 110 gtf["+"]["intergenic"] = [] |
| 114 gtf["-"]["intergenic"] = [] | 111 gtf["-"]["intergenic"] = [] |
| 115 for chr_strand in gtf_gene.keys(): | 112 for chr_strand in gtf_gene.keys(): |
| 116 chr = chr_strand.split("#")[0] | 113 chr = chr_strand.split("#")[0] |
| 117 strand = chr_strand.split("#")[1] | 114 strand = chr_strand.split("#")[1] |
| 118 start_list = gtf_gene[chr_strand][0] | 115 start_list = gtf_gene[chr_strand][0] |
| 119 end_list = gtf_gene[chr_strand][1] | 116 end_list = gtf_gene[chr_strand][1] |
| 120 gene_list = gtf_gene[chr_strand][2] | 117 gene_list = gtf_gene[chr_strand][2] |
| 121 sorted_start_index = [i[0] for i in sorted(enumerate(start_list), key=lambda x:x[1])] | 118 sorted_start_index = [i[0] for i in sorted(enumerate(start_list), key=lambda x:x[1])] |
| 122 sorted_end_index = [i[0] for i in sorted(enumerate(end_list), key=lambda x:x[1])] | 119 sorted_end_index = [i[0] for i in sorted(enumerate(end_list), key=lambda x:x[1])] |
| 123 | 120 |
| 124 sorted_start = sorted(start_list) | 121 sorted_start = sorted(start_list) |
| 125 sorted_end = [end_list[i] for i in sorted_start_index] | 122 sorted_end = [end_list[i] for i in sorted_start_index] |
| 126 sorted_gene = [gene_list[i] for i in sorted_start_index] | 123 sorted_gene = [gene_list[i] for i in sorted_start_index] |
| 127 for x in range(len(sorted_start))[1:]: | 124 for x in range(len(sorted_start))[1:]: |
| 128 intergene_start = sorted_end[x-1]+1 | 125 intergene_start = sorted_end[x - 1] + 1 |
| 129 intergene_end = sorted_start[x]-1 | 126 intergene_end = sorted_start[x] - 1 |
| 130 if intergene_start < intergene_end: | 127 if intergene_start < intergene_end: |
| 131 intergene_1 = sorted_gene[x-1] | 128 intergene_1 = sorted_gene[x - 1] |
| 132 intergene_2 = sorted_gene[x] | 129 intergene_2 = sorted_gene[x] |
| 133 gene = intergene_1 + "-#-" + intergene_2 | 130 gene = intergene_1 + "-#-" + intergene_2 |
| 134 data = (chr, str(intergene_start), str(intergene_end), gene, "", strand, "intergenic") | 131 data = (chr, str(intergene_start), str(intergene_end), gene, "", strand, "intergenic") |
| 135 gtf[strand]["intergenic"].append(data) | 132 gtf[strand]["intergenic"].append(data) |
| 136 | 133 |
| 137 import sqlite3 | 134 import sqlite3 |
| 138 # conn = sqlite3.connect('gtf_database.db') | 135 # conn = sqlite3.connect('gtf_database.db') |
| 139 conn = sqlite3.connect(":memory:") | 136 conn = sqlite3.connect(":memory:") |
| 140 c = conn.cursor() | 137 c = conn.cursor() |
| 141 # c.execute("DROP TABLE IF EXISTS gtf_data;") | 138 # c.execute("DROP TABLE IF EXISTS gtf_data;") |
| 142 # c.execute("CREATE TABLE IF NOT EXISTS gtf_data(chr text, start int, end int, gene text, transcript text, strand text, type text)") | 139 # c.execute("CREATE TABLE IF NOT EXISTS gtf_data(chr text, start int, end int, gene text, transcript text, strand text, type text)") |
| 143 c.execute("CREATE TABLE gtf_data(chr text, start int, end int, gene text, transcript text, strand text, type text)") | 140 c.execute("CREATE TABLE gtf_data(chr text, start int, end int, gene text, transcript text, strand text, type text)") |
| 144 | 141 |
| 145 for strand in gtf.keys(): | 142 for strand in gtf.keys(): |
| 146 if strand == "+": | 143 if strand not in ["+", "-"]: |
| 147 st = "positive" | 144 print("Please check the strand information in the GTF file. It should be '+' or '-'.") |
| 148 elif strand == "-": | 145 |
| 149 st = "negative" | |
| 150 else: | |
| 151 print "Please check the strand information in the GTF file. It should be '+' or '-'." | |
| 152 | |
| 153 for type in gtf[strand].keys(): | 146 for type in gtf[strand].keys(): |
| 154 data = gtf[strand][type] | 147 data = gtf[strand][type] |
| 155 c.executemany('INSERT INTO gtf_data VALUES (?,?,?,?,?,?,?)', data) | 148 c.executemany('INSERT INTO gtf_data VALUES (?,?,?,?,?,?,?)', data) |
| 156 | 149 |
| 157 conn.commit() | 150 conn.commit() |
| 158 | 151 |
| 159 infh = open(inputFile[2], "r") | 152 infh = open(inputFile[2], "r") |
| 160 # infh = open("Mouse_Data_All_peptides_withNewDBs.txt", "r") | 153 # infh = open("Mouse_Data_All_peptides_withNewDBs.txt", "r") |
| 161 data = infh.readlines() | 154 data = infh.readlines() |
| 162 # output file | 155 # output file |
| 163 outfh = open(inputFile[3], 'w') | 156 outfh = open(inputFile[3], 'w') |
| 164 # outfh = open("classified_1_Mouse_Data_All_peptides_withNewDBs.txt", "w") | 157 # outfh = open("classified_1_Mouse_Data_All_peptides_withNewDBs.txt", "w") |
| 165 | 158 |
| 166 for each in data: | 159 for each in data: |
| 167 a = each.strip().split("\t") | 160 a = each.strip().split("\t") |
| 168 chr = a[0].strip() | 161 chr = a[0].strip() |
| 169 pep_start = str(int(a[1].strip())+1) | 162 pep_start = str(int(a[1].strip()) + 1) |
| 170 pep_end = a[2].strip() | 163 pep_end = a[2].strip() |
| 171 strand = a[5].strip() | 164 strand = a[5].strip() |
| 172 each = "\t".join(a[:6]) | 165 each = "\t".join(a[:6]) |
| 173 if (len(a) == 12 and int(a[9]) == 1) or (len(a) == 6): | 166 if (len(a) == 12 and int(a[9]) == 1) or (len(a) == 6): |
| 174 c.execute("select * from gtf_data where type = 'CDS' and chr = '"+chr+"' and start <= "+pep_start+" and end >= "+pep_end+" and strand = '"+strand+"' ") | 167 c.execute("select * from gtf_data where type = 'CDS' and chr = '" + chr + "' and start <= " + pep_start + " and end >= " + pep_end + " and strand = '" + strand + "' ") |
| 175 rows = c.fetchall() | 168 rows = c.fetchall() |
| 176 if len(rows) > 0: | 169 if len(rows) > 0: |
| 177 outfh.write(each.strip() + "\tCDS\n") | 170 outfh.write(each.strip() + "\tCDS\n") |
| 178 else: | 171 else: |
| 179 c.execute("select * from gtf_data where type = 'five_prime_utr' and chr = '"+chr+"' and start <= "+pep_start+" and end >= "+pep_end+" and strand = '"+strand+"' ") | 172 c.execute("select * from gtf_data where type = 'five_prime_utr' and chr = '" + chr + "' and start <= " + pep_start + " and end >= " + pep_end + " and strand = '" + strand + "' ") |
| 180 rows = c.fetchall() | 173 rows = c.fetchall() |
| 181 if len(rows) > 0: | 174 if len(rows) > 0: |
| 182 outfh.write(each.strip() + "\tfive_prime_utr\n") | 175 outfh.write(each.strip() + "\tfive_prime_utr\n") |
| 183 else: | 176 else: |
| 184 c.execute("select * from gtf_data where type = 'three_prime_utr' and chr = '"+chr+"' and start <= "+pep_start+" and end >= "+pep_end+" and strand = '"+strand+"' ") | 177 c.execute("select * from gtf_data where type = 'three_prime_utr' and chr = '" + chr + "' and start <= " + pep_start + " and end >= " + pep_end + " and strand = '" + strand + "' ") |
| 185 rows = c.fetchall() | 178 rows = c.fetchall() |
| 186 if len(rows) > 0: | 179 if len(rows) > 0: |
| 187 outfh.write(each.strip() + "\tthree_prime_utr\n") | 180 outfh.write(each.strip() + "\tthree_prime_utr\n") |
| 188 else: | 181 else: |
| 189 c.execute("select * from gtf_data where type = 'exon' and chr = '"+chr+"' and start <= "+pep_start+" and end >= "+pep_end+" and strand = '"+strand+"' ") | 182 c.execute("select * from gtf_data where type = 'exon' and chr = '" + chr + "' and start <= " + pep_start + " and end >= " + pep_end + " and strand = '" + strand + "' ") |
| 190 rows = c.fetchall() | 183 rows = c.fetchall() |
| 191 if len(rows) > 0: | 184 if len(rows) > 0: |
| 192 outfh.write(each.strip() + "\texon\n") | 185 outfh.write(each.strip() + "\texon\n") |
| 193 else: | 186 else: |
| 194 c.execute("select * from gtf_data where type = 'intron' and chr = '"+chr+"' and start <= "+pep_start+" and end >= "+pep_end+" and strand = '"+strand+"' ") | 187 c.execute("select * from gtf_data where type = 'intron' and chr = '" + chr + "' and start <= " + pep_start + " and end >= " + pep_end + " and strand = '" + strand + "' ") |
| 195 rows = c.fetchall() | 188 rows = c.fetchall() |
| 196 if len(rows) > 0: | 189 if len(rows) > 0: |
| 197 outfh.write(each.strip() + "\tintron\n") | 190 outfh.write(each.strip() + "\tintron\n") |
| 198 else: | 191 else: |
| 199 c.execute("select * from gtf_data where type = 'gene' and chr = '"+chr+"' and start <= "+pep_start+" and end >= "+pep_end+" and strand = '"+strand+"' ") | 192 c.execute("select * from gtf_data where type = 'gene' and chr = '" + chr + "' and start <= " + pep_start + " and end >= " + pep_end + " and strand = '" + strand + "' ") |
| 200 rows = c.fetchall() | 193 rows = c.fetchall() |
| 201 if len(rows) > 0: | 194 if len(rows) > 0: |
| 202 outfh.write(each.strip() + "\tgene\n") | 195 outfh.write(each.strip() + "\tgene\n") |
| 203 else: | 196 else: |
| 204 c.execute("select * from gtf_data where type = 'intergenic' and chr = '"+chr+"' and start <= "+pep_start+" and end >= "+pep_end+" and strand = '"+strand+"' ") | 197 c.execute("select * from gtf_data where type = 'intergenic' and chr = '" + chr + "' and start <= " + pep_start + " and end >= " + pep_end + " and strand = '" + strand + "' ") |
| 205 rows = c.fetchall() | 198 rows = c.fetchall() |
| 206 if len(rows) > 0: | 199 if len(rows) > 0: |
| 207 outfh.write(each.strip() + "\tintergene\n") | 200 outfh.write(each.strip() + "\tintergene\n") |
| 208 else: | 201 else: |
| 209 outfh.write(each.strip() + "\tOVERLAPPING_ON_TWO_REGIONS: PLEASE_LOOK_MANUALLY (Will be updated in next version)\n") | 202 outfh.write(each.strip() + "\tOVERLAPPING_ON_TWO_REGIONS: PLEASE_LOOK_MANUALLY (Will be updated in next version)\n") |
| 210 elif (len(a) == 12 and int(a[9]) == 2): | 203 elif (len(a) == 12 and int(a[9]) == 2): |
| 211 outfh.write(each.strip() + "\tSpliceJunction\n") | 204 outfh.write(each.strip() + "\tSpliceJunction\n") |
| 212 else: | 205 else: |
| 213 outfh.write(each.strip() + "\tPlease check\n") | 206 outfh.write(each.strip() + "\tPlease check\n") |
| 214 | 207 |
| 215 conn.close() | 208 conn.close() |
| 216 outfh.close() | 209 outfh.close() |
| 217 else: | 210 else: |
| 218 print "USAGE: python pep_pointer.py <input GTF file> <input tblastn file> <name of output file>" | 211 print("USAGE: python pep_pointer.py <input GTF file> <input tblastn file> <name of output file>") |
| 219 return None | 212 return None |
| 213 | |
| 220 | 214 |
| 221 if __name__ == "__main__": | 215 if __name__ == "__main__": |
| 222 main() | 216 main() |
| 223 | |
| 224 | |
| 225 | |
| 226 | |
| 227 |
