Mercurial > repos > vipints > deseq_hts
view deseq-hts_1.0/tools/ParseGFF.py @ 0:94a108763d9e draft
deseq-hts version 1.0 wraps the DESeq 1.6.0
author | vipints |
---|---|
date | Wed, 09 May 2012 20:43:47 -0400 |
parents | |
children | 8ab01cc29c4b |
line wrap: on
line source
#!/usr/bin/env python """ Extract genome annotation from a GFF3 (a tab delimited format for storing sequence features and annotations: http://www.sequenceontology.org/gff3.shtml) file. Usage: ParseGFF.py in.gff3 out.mat Requirements: Scipy :- http://scipy.org/ Numpy :- http://numpy.org/ Copyright (C) 2010-2012 Friedrich Miescher Laboratory of the Max Planck Society, Tubingen, Germany """ import re, sys, os import scipy.io as sio import numpy as np def createExon(strand_p, five_p_utr, cds_cod, three_p_utr): """Create exon cordinates from UTR's and CDS region """ exon_pos = [] if strand_p == '+': utr5_start, utr5_end = 0, 0 if five_p_utr != []: utr5_start, utr5_end = five_p_utr[-1][0], five_p_utr[-1][1] cds_5start, cds_5end = cds_cod[0][0], cds_cod[0][1] jun_exon = [] if cds_5start-utr5_end == 0 or cds_5start-utr5_end == 1: jun_exon = [utr5_start, cds_5end] if len(cds_cod) == 1: five_prime_flag = 0 if jun_exon != []: five_p_utr = five_p_utr[:-1] five_prime_flag = 1 for utr5 in five_p_utr: exon_pos.append(utr5) jun_exon = [] utr3_start, utr3_end = 0, 0 if three_p_utr != []: utr3_start = three_p_utr[0][0] utr3_end = three_p_utr[0][1] if utr3_start-cds_5end == 0 or utr3_start-cds_5end == 1: jun_exon = [cds_5start, utr3_end] three_prime_flag = 0 if jun_exon != []: cds_cod = cds_cod[:-1] three_p_utr = three_p_utr[1:] three_prime_flag = 1 if five_prime_flag == 1 and three_prime_flag == 1: exon_pos.append([utr5_start, utr3_end]) if five_prime_flag == 1 and three_prime_flag == 0: exon_pos.append([utr5_start, cds_5end]) cds_cod = cds_cod[:-1] if five_prime_flag == 0 and three_prime_flag == 1: exon_pos.append([cds_5start, utr3_end]) for cds in cds_cod: exon_pos.append(cds) for utr3 in three_p_utr: exon_pos.append(utr3) else: if jun_exon != []: five_p_utr = five_p_utr[:-1] cds_cod = cds_cod[1:] for utr5 in five_p_utr: exon_pos.append(utr5) exon_pos.append(jun_exon) if jun_exon != [] else '' jun_exon = [] utr3_start, utr3_end = 0, 0 if three_p_utr != []: utr3_start = three_p_utr[0][0] utr3_end = three_p_utr[0][1] cds_3start = cds_cod[-1][0] cds_3end = cds_cod[-1][1] if utr3_start-cds_3end == 0 or utr3_start-cds_3end == 1: jun_exon = [cds_3start, utr3_end] if jun_exon != []: cds_cod = cds_cod[:-1] three_p_utr = three_p_utr[1:] for cds in cds_cod: exon_pos.append(cds) exon_pos.append(jun_exon) if jun_exon != [] else '' for utr3 in three_p_utr: exon_pos.append(utr3) elif strand_p == '-': utr3_start, utr3_end = 0, 0 if three_p_utr != []: utr3_start = three_p_utr[-1][0] utr3_end = three_p_utr[-1][1] cds_3start = cds_cod[0][0] cds_3end = cds_cod[0][1] jun_exon = [] if cds_3start-utr3_end == 0 or cds_3start-utr3_end == 1: jun_exon = [utr3_start, cds_3end] if len(cds_cod) == 1: three_prime_flag = 0 if jun_exon != []: three_p_utr = three_p_utr[:-1] three_prime_flag = 1 for utr3 in three_p_utr: exon_pos.append(utr3) jun_exon = [] (utr5_start, utr5_end) = (0, 0) if five_p_utr != []: utr5_start = five_p_utr[0][0] utr5_end = five_p_utr[0][1] if utr5_start-cds_3end == 0 or utr5_start-cds_3end == 1: jun_exon = [cds_3start, utr5_end] five_prime_flag = 0 if jun_exon != []: cds_cod = cds_cod[:-1] five_p_utr = five_p_utr[1:] five_prime_flag = 1 if three_prime_flag == 1 and five_prime_flag == 1: exon_pos.append([utr3_start, utr5_end]) if three_prime_flag == 1 and five_prime_flag == 0: exon_pos.append([utr3_start, cds_3end]) cds_cod = cds_cod[:-1] if three_prime_flag == 0 and five_prime_flag == 1: exon_pos.append([cds_3start, utr5_end]) for cds in cds_cod: exon_pos.append(cds) for utr5 in five_p_utr: exon_pos.append(utr5) else: if jun_exon != []: three_p_utr = three_p_utr[:-1] cds_cod = cds_cod[1:] for utr3 in three_p_utr: exon_pos.append(utr3) if jun_exon != []: exon_pos.append(jun_exon) jun_exon = [] (utr5_start, utr5_end) = (0, 0) if five_p_utr != []: utr5_start = five_p_utr[0][0] utr5_end = five_p_utr[0][1] cds_5start = cds_cod[-1][0] cds_5end = cds_cod[-1][1] if utr5_start-cds_5end == 0 or utr5_start-cds_5end == 1: jun_exon = [cds_5start, utr5_end] if jun_exon != []: cds_cod = cds_cod[:-1] five_p_utr = five_p_utr[1:] for cds in cds_cod: exon_pos.append(cds) if jun_exon != []: exon_pos.append(jun_exon) for utr5 in five_p_utr: exon_pos.append(utr5) return exon_pos def init_gene(): """Initializing the gene structure """ gene_details=dict(chr='', exons=[], gene_info={}, id='', is_alt_spliced=0, name='', source='', start='', stop='', strand='', transcripts=[]) return gene_details def FeatureValueFormat(singlegene): """Make feature value compactable to write in a .mat format """ comp_exon = np.zeros((len(singlegene['exons']),), dtype=np.object) for i in range(len(singlegene['exons'])): comp_exon[i]= np.array(singlegene['exons'][i]) singlegene['exons'] = comp_exon comp_transcripts = np.zeros((len(singlegene['transcripts']),), dtype=np.object) for i in range(len(singlegene['transcripts'])): comp_transcripts[i] = np.array(singlegene['transcripts'][i]) singlegene['transcripts'] = comp_transcripts return singlegene def CreateGeneModels(genes_cmpt, transcripts_cmpt, exons_cmpt, utr3_cmpt, utr5_cmpt, cds_cmpt): """Creating Coding/Non-coding gene models from parsed GFF objects. """ gene_counter, gene_models=1, [] for gene_entry in genes_cmpt: ## Figure out the genes and transcripts associated feature if gene_entry in transcripts_cmpt: gene=init_gene() gene['id']=gene_counter gene['name']=gene_entry[1] gene['chr']=genes_cmpt[gene_entry]['chr'] gene['source']=genes_cmpt[gene_entry]['source'] gene['start']=genes_cmpt[gene_entry]['start'] gene['stop']=genes_cmpt[gene_entry]['stop'] gene['strand']=genes_cmpt[gene_entry]['strand'] if not gene['strand'] in ['+', '-']: gene['strand']='.' # Strand info not known replaced with a dot symbol instead of None, ?, . etc. gene['gene_info']=dict(ID=gene_entry[1]) if len(transcripts_cmpt[gene_entry])>1: gene['is_alt_spliced'] = 1 for tids in transcripts_cmpt[gene_entry]: ## transcript section related tags gene['transcripts'].append(tids['ID']) if len(exons_cmpt) != 0: if (gene['chr'], tids['ID']) in exons_cmpt: exon_cod=[[feat_exon['start'], feat_exon['stop']] for feat_exon in exons_cmpt[(gene['chr'], tids['ID'])]] else: ## build exon coordinates from UTR3, UTR5 and CDS utr5_pos, cds_pos, utr3_pos = [], [], [] if (gene['chr'], tids['ID']) in utr5_cmpt: utr5_pos=[[feat_utr5['start'], feat_utr5['stop']] for feat_utr5 in utr5_cmpt[(gene['chr'], tids['ID'])]] if (gene['chr'], tids['ID']) in cds_cmpt: cds_pos=[[feat_cds['start'], feat_cds['stop']] for feat_cds in cds_cmpt[(gene['chr'], tids['ID'])]] if (gene['chr'], tids['ID']) in utr3_cmpt: utr3_pos=[[feat_utr3['start'], feat_utr3['stop']] for feat_utr3 in utr3_cmpt[(gene['chr'], tids['ID'])]] exon_cod=createExon(gene['strand'], utr5_pos, cds_pos, utr3_pos) if gene['strand']=='-': if len(exon_cod) >1: if exon_cod[0][0] > exon_cod[-1][0]: exon_cod.reverse() if exon_cod: gene['exons'].append(exon_cod) gene=FeatureValueFormat(gene) # get prepare for MAT writing gene_counter+=1 gene_models.append(gene) return gene_models def GFFParse(gff_file): """Parsing GFF file based on feature relationship. """ genes, utr5, exons=dict(), dict(), dict() transcripts, utr3, cds=dict(), dict(), dict() # TODO Include growing key words of different non-coding/coding transcripts features=['mRNA', 'transcript', 'ncRNA', 'miRNA', 'pseudogenic_transcript', 'rRNA', 'snoRNA', 'snRNA', 'tRNA', 'scRNA'] gff_handle=open(gff_file, "rU") for gff_line in gff_handle: gff_line=gff_line.strip('\n\r').split('\t') if re.match(r'#|>', gff_line[0]): # skip commented line and fasta identifier line continue if len(gff_line)==1: # skip fasta sequence/empty line if present continue assert len(gff_line)==9, '\t'.join(gff_line) # not found 9 tab-delimited fields in this line if '' in gff_line: # skip this line if there any field with an empty value print 'Skipping..', '\t'.join(gff_line) continue if gff_line[-1][-1]==';': # trim the last ';' character gff_line[-1]=gff_line[-1].strip(';') if gff_line[2] in ['gene', 'pseudogene']: gid, gene_info=None, dict() gene_info['start']=int(gff_line[3]) gene_info['stop']=int(gff_line[4]) gene_info['chr']=gff_line[0] gene_info['source']=gff_line[1] gene_info['strand']=gff_line[6] for attb in gff_line[-1].split(';'): attb=attb.split('=') # gff attributes are separated by key=value pair if attb[0]=='ID': gid=attb[1] break genes[(gff_line[0], gid)]=gene_info # store gene information based on the chromosome and gene symbol. elif gff_line[2] in features: gid, mrna_info=None, dict() mrna_info['start']=int(gff_line[3]) mrna_info['stop']=int(gff_line[4]) mrna_info['chr']=gff_line[0] mrna_info['strand']=gff_line[6] for attb in gff_line[-1].split(';'): attb=attb.split('=') if attb[0]=='Parent': gid=attb[1] elif attb[0]=='ID': mrna_info[attb[0]]=attb[1] for fid in gid.split(','): # child may be mapped to multiple parents ex: Parent=AT01,AT01-1-Protein if (gff_line[0], fid) in transcripts: transcripts[(gff_line[0], fid)].append(mrna_info) else: transcripts[(gff_line[0], fid)]=[mrna_info] elif gff_line[2] in ['exon']: tids, exon_info=None, dict() exon_info['start']=int(gff_line[3]) exon_info['stop']=int(gff_line[4]) exon_info['chr']=gff_line[0] exon_info['strand']=gff_line[6] for attb in gff_line[-1].split(';'): attb=attb.split('=') if attb[0]=='Parent': tids=attb[1] break for tid in tids.split(','): if (gff_line[0], tid) in exons: exons[(gff_line[0], tid)].append(exon_info) else: exons[(gff_line[0], tid)]=[exon_info] elif gff_line[2] in ['five_prime_UTR']: utr5_info, tids=dict(), None utr5_info['start']=int(gff_line[3]) utr5_info['stop']=int(gff_line[4]) utr5_info['chr']=gff_line[0] utr5_info['strand']=gff_line[6] for attb in gff_line[-1].split(';'): attb=attb.split('=') if attb[0]=='Parent': tids=attb[1] break for tid in tids.split(','): if (gff_line[0], tid) in utr5: utr5[(gff_line[0], tid)].append(utr5_info) else: utr5[(gff_line[0], tid)]=[utr5_info] elif gff_line[2] in ['CDS']: cds_info, tids=dict(), None cds_info['start']=int(gff_line[3]) cds_info['stop']=int(gff_line[4]) cds_info['chr']=gff_line[0] cds_info['strand']=gff_line[6] for attb in gff_line[-1].split(';'): attb=attb.split('=') if attb[0]=='Parent': tids=attb[1] break for tid in tids.split(','): if (gff_line[0], tid) in cds: cds[(gff_line[0], tid)].append(cds_info) else: cds[(gff_line[0], tid)]=[cds_info] elif gff_line[2] in ['three_prime_UTR']: utr3_info, tids=dict(), None utr3_info['start']=int(gff_line[3]) utr3_info['stop']=int(gff_line[4]) utr3_info['chr']=gff_line[0] utr3_info['strand']=gff_line[6] for attb in gff_line[-1].split(';'): attb=attb.split('=') if attb[0]=='Parent': tids=attb[1] break for tid in tids.split(','): if (gff_line[0], tid) in utr3: utr3[(gff_line[0], tid)].append(utr3_info) else: utr3[(gff_line[0], tid)]=[utr3_info] gff_handle.close() return genes, transcripts, exons, utr3, utr5, cds def __main__(): """This function provides a best way to extract genome feature information from a GFF3 file for the rQuant downstream processing. """ try: gff_file = sys.argv[1] mat_file = sys.argv[2] except: print __doc__ sys.exit(-1) genes, transcripts, exons, utr3, utr5, cds=GFFParse(gff_file) gene_models=CreateGeneModels(genes, transcripts, exons, utr3, utr5, cds) # TODO Write to matlab/octave struct instead of cell arrays. sio.savemat(mat_file, mdict=dict(genes=gene_models), format='5', oned_as='row') if __name__=='__main__': __main__()