diff fml_gff_groomer/scripts/gff_loci_merge.py @ 0:79726c328621 default tip

Migrated tool version 1.0.0 from old tool shed archive to new tool shed repository

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/fml_gff_groomer/scripts/gff_loci_merge.py	Tue Jun 07 17:29:24 2011 -0400
@@ -0,0 +1,300 @@
+#!/usr/bin/env python
+#
+# This program is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 3 of the License, or
+# (at your option) any later version.
+#
+# Written (W) 2010 Vipin T Sreedharan, Friedrich Miescher Laboratory of the Max Planck Society
+# Copyright (C) 2010 Friedrich Miescher Laboratory of the Max Planck Society
+#
+# Description : to merge same transcripts in single loci and define as an alternative spliced form for the gene.
+
+def display_content(final_dict):
+    """displaying the summary from GFF file"""
+
+    print "\tUnique combination of Source(s), Feature type(s) and corresponding count:"
+    for sftype, cnt in sorted(final_dict['gff_source_type'].items()):
+        if sftype[1] == 'gene':print '\t' + str(cnt) + '\t' + str(sftype[0]) + ', '+ str(sftype[1])
+
+def available_limits(gff_file):
+    """Figure out the available feature types from the given GFF file"""
+    
+    gff_handle = open(gff_file, 'rU')
+    filter_info = dict(gff_id = [0], gff_source_type = [1, 2],
+                gff_source = [1], gff_type = [2])
+    cur_limits = dict()
+    for filter_key in filter_info.keys():
+        cur_limits[filter_key] = collections.defaultdict(int)
+    for line in gff_handle:
+        if line.strip('\n\r')[0] != "#":
+            parts = [p.strip() for p in line.split('\t')]
+            if len(parts) == 1 and re.search(r'\w+', parts[0]):continue ## GFF files with FASTA sequence together 
+            assert len(parts) == 9, line
+            for filter_key, cur_indexes in filter_info.items():
+                cur_id = tuple([parts[i] for i in cur_indexes])
+                cur_limits[filter_key][cur_id] += 1
+    # get rid of the default dicts
+    gff_handle.close()
+    final_dict = dict()
+    for key, value_dict in cur_limits.items():
+        if len(key) == 1:key = key[0]
+        final_dict[key] = dict(value_dict)
+    return final_dict
+
+def GFFWriter(merged_info, genes, transcripts, exons, utr5, cds, utr3, out_file):
+    """Write GFF3 file with merged feature description"""
+    
+    out_fh = open(out_file, 'w')
+    for ginfo, regions in merged_info.items():
+        gene_cnt = 1
+        for interval, features in sorted(regions.items()):# master gene feature
+            out_fh.write(ginfo[0] + '\t' + ginfo[1] + '\tgene\t' + str(interval[0]) + '\t' + str(interval[1]) + '\t.\t' + ginfo[2] + '\t.\tID=Gene_' + ginfo[0] + '_' + str(gene_cnt).zfill(5) + ';Name=Gene_' + ginfo[0] + '_' + str(gene_cnt).zfill(5) + '\n')
+            for geneid in features:# corresponding transcript info 
+                if geneid in transcripts:
+                    for tinfo in transcripts[geneid]:# transcript feature line 
+                        out_fh.write(ginfo[0] + '\t' + ginfo[1] + '\t' + tinfo['type'] + '\t' + str(tinfo['start']) + '\t' + str(tinfo['stop']) + '\t.\t' + ginfo[2] + '\t.\tID=' + tinfo['ID']+ ';Parent=Gene_' + ginfo[0] + '_' + str(gene_cnt).zfill(5) + '\n')
+                        if tinfo['ID'] in utr5:# check for 5 prime UTR 
+                            for u5info in utr5[tinfo['ID']]:out_fh.write(ginfo[0] + '\t' + ginfo[1] + '\tfive_prime_UTR\t' + str(u5info['start']) + '\t' + str(u5info['stop']) + '\t.\t' + ginfo[2] + '\t.\tParent=' + tinfo['ID'] + '\n')
+                        if tinfo['ID'] in cds:# check for CDS 
+                            for cdsinfo in cds[tinfo['ID']]:out_fh.write(ginfo[0] + '\t' + ginfo[1] + '\tCDS\t' + str(cdsinfo['start']) + '\t' + str(cdsinfo['stop']) + '\t.\t' + ginfo[2] + '\t.\tParent=' + tinfo['ID'] + '\n')
+                        if tinfo['ID'] in utr3:# check for 3 prime UTR
+                            for u3info in utr3[tinfo['ID']]:out_fh.write(ginfo[0] + '\t' + ginfo[1] + '\tthree_prime_UTR\t' + str(u3info['start']) + '\t' + str(u3info['stop']) + '\t.\t' + ginfo[2] + '\t.\tParent=' + tinfo['ID'] + '\n')
+                        if tinfo['ID'] in exons:# check for exons
+                            for exinfo in exons[tinfo['ID']]:out_fh.write(ginfo[0] + '\t' + ginfo[1] + '\texon\t' + str(exinfo['start']) + '\t' + str(exinfo['stop']) + '\t.\t' + ginfo[2] + '\t.\tParent=' + tinfo['ID'] + '\n')
+            gene_cnt += 1
+    out_fh.close()
+
+def UniqLoci(genes, transcripts, exons):
+    """determine unique location where features annotated multiple times"""
+
+    uniq_loci = dict()
+    for gid, parts in genes.items():
+        gene_info = (parts['chr'], parts['source'], parts['strand'])
+        if gene_info in uniq_loci:## same contig, orientation, source: look for merging transcripts based on the nearby location
+            if (int(parts['start']), int(parts['stop'])) in uniq_loci[gene_info].keys(): ## similar transcripts will catch here (start and stop are same may be exon, CDS or intron content may vary) 
+                uniq_loci[gene_info][(int(parts['start']), int(parts['stop']))].append(gid)
+            else: # heuristic approach to include closely related region on a single master loci.
+                got_a_range = 0
+                for floc in uniq_loci[gene_info].keys():# look whether it lies closely to any intervel which is already defined  
+                    if (floc[1]-parts['start']) < 150 or (parts['stop']-floc[0]) < 150:continue ## TODO boundary spanning length in same orientation for genes of each species will be great.
+                    if floc[0] <= parts['start'] and parts['start'] < floc[1]: # the start of the new candidate is inside of any of the already defined interval ?
+                        non_coding = 0
+                        try: # check for small transcript whether they belong to a existing one or a new non-coding candidate.  
+                            if len(transcripts[gid]) == 1: 
+                                if len(exons[transcripts[gid][0]['ID']]) == 1:non_coding = 1
+                            if non_coding == 0:
+                                if parts['stop'] > floc[1]:# making global gene coordinate from individual transcript model
+                                    entries = uniq_loci[gene_info][floc]
+                                    del uniq_loci[gene_info][floc] # remove the existing interval, here we got a longer downstream position from the candidate
+                                    entries.append(gid)
+                                    uniq_loci[gene_info][(floc[0], parts['stop'])] = entries
+                                else:
+                                    uniq_loci[gene_info][floc].append(gid)
+                            else:# create a new interval for non-coding type entry 
+                                uniq_loci[gene_info][(parts['start'], parts['stop'])] = [gid] 
+                            got_a_range = 1
+                            break
+                        except: # dont have any transcripts or exons defined.
+                            break
+                    elif floc[0] < parts['stop'] and parts['stop'] <= floc[1]: # the stop of the new candidate is inside of any of the pre-defined interval ? the candidate seems to be from more upstream
+                        non_coding = 0
+                        try:
+                            if len(transcripts[gid]) == 1: 
+                                if len(exons[transcripts[gid][0]['ID']]) == 1:non_coding = 1
+                            if non_coding == 0:
+                                entries = uniq_loci[gene_info][floc]
+                                del uniq_loci[gene_info][floc] # remove the existing interval, here we got a upstream position from which the candidate transcribing 
+                                entries.append(gid)
+                                uniq_loci[gene_info][(int(parts['start']), floc[1])] = entries
+                            else: # create a new interval for non-coding type entry 
+                                uniq_loci[gene_info][(parts['start'], parts['stop'])] = [gid] 
+                            got_a_range = 1
+                            break
+                        except:
+                            break
+                    elif floc[0] > parts['start'] and floc[1] < parts['stop']: # whether the whole feature floc region (--) resides in the candidate location (----------) ? 
+                        non_coding = 0 # here the candidate seems to be longer than the pre-defined interval, check all entries from the pre-defined interval whether it is a small region, any chance as non-coding.
+                        try:
+                            for features in uniq_loci[gene_info][floc]:
+                                if len(transcripts[features]) == 1:
+                                    if len(exons[transcripts[features][0]['ID']]) == 1:non_coding = 1
+                            if non_coding == 1: # create a new interval for non coding 
+                                uniq_loci[gene_info][(parts['start'], parts['stop'])] = [gid]
+                            else: # append the existing transcript cluster, here change the interval position based on the candidate location 
+                                entries = uniq_loci[gene_info][floc]
+                                del uniq_loci[gene_info][floc] # remove the existing interval, here we got a longer upstream and downstream region.
+                                entries.append(gid)
+                                uniq_loci[gene_info][(parts['start'], parts['stop'])] = entries
+                            got_a_range = 1
+                            break
+                        except:
+                            break
+                ## or create a new interval ?? 
+                if got_a_range == 0:uniq_loci[gene_info][(parts['start'], parts['stop'])] = [gid]
+        else:
+            uniq_loci[gene_info] = {(int(parts['start']), int(parts['stop'])): [gid]}
+
+    return uniq_loci
+
+def ParseGFF(gff_file):
+    """feature extraction from provided GFF file"""
+
+    gff_handle = open(gff_file, 'rU')
+    genes, transcripts, exons, utr5, cds, utr3 = dict(), dict(), dict(), dict(), dict(), dict()
+    for gff_line in gff_handle:
+        parts = gff_line.strip('\n\r').split('\t')
+        if gff_line[0] == '#' or gff_line[0] == '>':continue
+        if len(parts) == 1:continue ## Some centers in the world create GFF files with FASTA sequence together 
+        if len(parts) != 9:sys.stdout.write('Warning: Found invalid GFF line\n' + gff_line.strip('\n\r') + '\n');continue
+        if parts[3] == '' or parts[4] == '':sys.stdout.write('Warning: Found missing coordinate in GFF line\n' + gff_line.strip('\n\r') + '\n');continue
+        if parts[2] == 'gene':
+            gene_info = dict()
+            gene_info['start'] = int(parts[3])
+            gene_info['stop'] = int(parts[4])
+            gene_info['chr'] = parts[0]
+            gene_info['source'] = parts[1]
+            gene_info['strand'] = parts[6]
+            gid = ''
+            for attr in parts[-1].split(';'):
+                if attr == '':continue ## GFF line may end with a ';' symbol
+                attr = attr.split('=')
+                if attr[0] == 'ID':gid=attr[1];continue 
+                gene_info[attr[0]] = attr[1]
+            if gid != '': genes[gid] = gene_info
+        if parts[2] == 'mRNA' or parts[2] == 'transcript' or parts[2] == 'ncRNA' or parts[2] == 'tRNA' or parts[2] == 'snRNA' or parts[2] == 'scRNA' or parts[2] == 'snoRNA' or parts[2] == 'snlRNA' or parts[2] == 'rRNA' or parts[2] == 'miRNA':
+            mrna_info = dict() 
+            mrna_info['start'] = int(parts[3])
+            mrna_info['stop'] = int(parts[4])
+            mrna_info['chr'] =  parts[0]
+            mrna_info['strand'] = parts[6]
+            mrna_info['type'] = parts[2]
+            gid = ''
+            for attr in parts[-1].split(';'):
+                if attr == '':continue ## GFF line may end with a ';' symbol
+                attr = attr.split('=')
+                if attr[0] == 'Parent':gid=attr[1];continue
+                mrna_info[attr[0]] = attr[1]
+            if gid in transcripts:
+                transcripts[gid].append(mrna_info)
+            else:
+                transcripts[gid] = [mrna_info]
+        if parts[2] == 'exon':
+            exon_info = dict()
+            exon_info['start'] = int(parts[3])
+            exon_info['stop'] = int(parts[4])
+            exon_info['chr'] =  parts[0]
+            exon_info['strand'] = parts[6]
+            tid = ''
+            for attr in parts[-1].split(';'):
+                if attr == '':continue ## GFF line may end with a ';' symbol
+                attr = attr.split('=')
+                if attr[0] == 'Parent':tid=attr[1];continue
+                exon_info[attr[0]] = attr[1]
+            if tid in exons:
+                exons[tid].append(exon_info)
+            else:
+                exons[tid] = [exon_info]
+        if parts[2] == 'five_prime_UTR':
+            utr5_info = dict()
+            utr5_info['start'] = int(parts[3])
+            utr5_info['stop'] = int(parts[4])
+            utr5_info['chr'] =  parts[0]
+            utr5_info['strand'] = parts[6]
+            tid = ''
+            for attr in parts[-1].split(';'):
+                if attr == '':continue ## GFF line may end with a ';' symbol
+                attr = attr.split('=')
+                if attr[0] == 'Parent':tid=attr[1];continue
+                utr5_info[attr[0]] = attr[1]
+            if tid in utr5:
+                utr5[tid].append(utr5_info)
+            else:
+                utr5[tid] = [utr5_info]
+        if parts[2] == 'CDS':
+            cds_info = dict()
+            cds_info['start'] = int(parts[3])
+            cds_info['stop'] = int(parts[4])
+            cds_info['chr'] =  parts[0]
+            cds_info['strand'] = parts[6]
+            tid = ''
+            for attr in parts[-1].split(';'):
+                if attr == '':continue
+                attr = attr.split('=')
+                if attr[0] == 'Parent':tid=attr[1];continue
+                cds_info[attr[0]] = attr[1]
+            if tid in cds:
+                cds[tid].append(cds_info)
+            else:
+                cds[tid] = [cds_info]
+        if parts[2] == 'three_prime_UTR':
+            utr3_info = dict()
+            utr3_info['start'] = int(parts[3])
+            utr3_info['stop'] = int(parts[4])
+            utr3_info['chr'] =  parts[0]
+            utr3_info['strand'] = parts[6]
+            tid = ''
+            for attr in parts[-1].split(';'):
+                if attr == '':continue
+                attr = attr.split('=')
+                if attr[0] == 'Parent':tid=attr[1];continue
+                utr3_info[attr[0]] = attr[1]
+            if tid in utr3:
+                utr3[tid].append(utr3_info)
+            else:
+                utr3[tid] = [utr3_info]
+    gff_handle.close()
+    return genes, transcripts, exons, utr5, cds, utr3
+
+import re, sys 
+import time 
+import collections
+
+if __name__=='__main__':
+    
+    stime = time.asctime( time.localtime(time.time()) )
+    print '-------------------------------------------------------'
+    print 'MergeLoci started on ' + stime
+    print '-------------------------------------------------------'
+    try:
+        gff_file = sys.argv[1]
+        out_file = sys.argv[2]
+    except:
+        sys.stderr.write("Missing GFF3 file, result file. terminating...\n")
+        sys.stderr.write("USAGE: gff_loci_merge.py <gff file> <result file>\n")
+        sys.exit(-1)
+    print '--------'
+    print 'Level: 1- ' + 'Reading GFF file: ' + re.sub(r'/home/galaxy/galaxy-2.1.2009', r'GALAXYDIR', gff_file)
+    print '--------'
+    print '--------'
+    print 'Level: 2- ' + 'BEFORE processing, Merging feature distribution in GFF file'
+    print '--------'
+    # initial feature distribution in file
+    final_dict = available_limits(gff_file)
+    display_content(final_dict)
+    # determine the whole content from GFF file 
+    genes, transcripts, exons, utr5, cds, utr3 = ParseGFF(gff_file)
+    print '--------'
+    print 'Level: 3- ' + 'Start merging feature(s) from similar locations...'
+    print '--------'
+    # determine the same gene loci on specific chromosome based on the same source
+    merged_regions = UniqLoci(genes, transcripts, exons)
+    print '\tDone.'
+    print '--------'
+    print 'Level: 4- ' + 'Writing merged feature annotation to GFF format...' 
+    print '--------'
+    # write new GFF file with merged loci information for gene feature
+    GFFWriter(merged_regions, genes, transcripts, exons, utr5, cds, utr3, out_file)
+    print '\tDone.'
+    # after processing display the feature distribution in the result file 
+    print '--------'
+    print 'Level: 5- ' + 'Merged feature(s) summary from GFF file' 
+    print '--------'
+    final_dict = available_limits(out_file)
+    display_content(final_dict)
+	print 
+    print '\tMerged result file: ' + re.sub(r'/home/galaxy/galaxy-2.1.2009', r'GALAXYDIR', out_file)
+    stime = time.asctime( time.localtime(time.time()) )
+    print '-------------------------------------------------------'
+    print 'MergeLoci finished at ' + stime
+    print '-------------------------------------------------------'