diff trams.py @ 4:bd5692103d5b draft

Uploaded
author rreumerman
date Fri, 05 Apr 2013 05:00:40 -0400
parents
children 8de0ffc2166f
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/trams.py	Fri Apr 05 05:00:40 2013 -0400
@@ -0,0 +1,497 @@
+#################
+transl_table = 11
+intro_message = ''' +------------------------------------------------------------------+
+ | Tool for Rapid Annotation of Microbial SNPs (TRAMS): a simple    |
+ | program for rapid annotation of genomic variation in prokaryotes |
+ |                                                                  |
+ | Developed by: Richard A. Reumerman, Paul R. Herron,              |
+ | Paul A. Hoskisson and Vartul Sangal                              |
+ +------------------------------------------------------------------+\n'''
+#################
+
+import sys
+import time
+start = time.clock()
+
+# Command line files: SNP REF REF-TYPE ANNOT OVERL SUM;
+if len(sys.argv) < 7:
+    exit("\nNot enough arguments given.\nUsage: TRAMS_Galaxy.py [SNP.] [REF.] [ANNOT.] [OVERL.] [SUM.]")
+try:
+    file_snps = open(sys.argv[1], "rU")
+except IOError as e:
+    exit("Error trying to open '"+sys.argv[1]+"': {1}".format(e.errno, e.strerror))
+try:
+    file_ref = open(sys.argv[2], "rU")
+except IOError as e:
+    exit("Error trying to open '"+sys.argv[2]+"': {1}".format(e.errno, e.strerror))
+
+filetype_reference = sys.argv[3]
+
+try:
+    file_out = open(sys.argv[4], "w")
+except IOError as e:
+    exit("Error trying to open '"+sys.argv[4]+"': {1}".format(e.errno, e.strerror))
+try:
+    file_overlap = open(sys.argv[5], "w")
+except IOError as e:
+    exit("Error trying to open '"+sys.argv[5]+"': {1}".format(e.errno, e.strerror))
+try:
+    file_summary = open(sys.argv[6], "w")
+except IOError as e:
+    exit("Error trying to open '"+sys.argv[6]+"': {1}".format(e.errno, e.strerror))
+
+import Bio
+from Bio import SeqIO, SeqFeature
+from Bio.SeqRecord import SeqRecord
+from Bio.Seq import Seq
+from Bio.Alphabet import generic_dna, IUPAC
+from Bio.Data import CodonTable
+
+modules_loaded = time.clock()
+
+def non_coding_calc(gene, pos = 0):
+    '''This function takes a pseudogene and returns the number of bases
+    located in between the sub-features before 'pos'. Returns 0 if 'pseudo' = False.
+    Input: {start, subfeats, pseudo}, pos (default = 0)'''
+    if not gene['pseudo']: return 0
+    
+    non_coding_bases = 0
+    prev_subfeat_end = gene['start']
+    if gene['strand'] == -1:
+        for subfeature in gene['subfeats']:
+            if subfeature.location._start.position < pos:
+                prev_subfeat_end = subfeature.location._end.position
+                continue
+            non_coding_bases += (subfeature.location._start.position - prev_subfeat_end)
+            prev_subfeat_end = subfeature.location._end.position
+    else:
+        for subfeature in gene['subfeats']:
+            non_coding_bases += (subfeature.location._start.position - prev_subfeat_end)
+            prev_subfeat_end = subfeature.location._end.position
+            if prev_subfeat_end >= pos and pos != 0: break
+
+    return non_coding_bases
+
+
+def region_calc(bounds,length):
+    regions = []
+    lastend=i=0
+    while i < len(bounds):
+        if bounds[i]['start'] > lastend:# Intergenic region present;
+            regions.append([lastend,bounds[i]['start'],-1])
+            lastend = bounds[i]['start']
+        else:
+            regions.append([bounds[i]['start'],bounds[i]['end'],i])
+            if bounds[i]['end'] > lastend:
+                lastend = bounds[i]['end']
+            i += 1
+
+    if regions[-1][1] < length:# Final tail of genome;
+        regions.append([lastend,length,-1])
+
+    return regions
+        
+
+def overlap_calc(bounds):
+    '''This function takes an array of feature starts and ends and
+    returns an array of starts and ends of all overlapping regions.
+    Input: [{start,end}]'''
+    i = 0
+    overlaps = []
+    while i < len(bounds) - 1:
+        for downstr in bounds[i+1:]:
+            if downstr[0] < bounds[i][1]:# Features overlap;
+                if downstr[1] < bounds[i][1]:# Complete overlap;
+                    overlaps.append([downstr[0],downstr[1],bounds[i][2],downstr[2],[0,0]])
+                else:# Partial overlap;
+                    overlaps.append([downstr[0],bounds[i][1],bounds[i][2],downstr[2],[0,0]])
+            else:# No use looking further;
+                break
+                
+        i += 1
+
+    return overlaps
+
+
+def match_feature(bounds,pos,prev=0):
+    '''This function checks if a position is located inside a feature and
+    returns the feature's number if found or -1 if none is found.
+    Input: {start,end},pos,prev_feat (default = 0)'''
+    for i in range(prev, len(bounds)):
+        if (pos >= bounds[i]['start']) and (pos < bounds[i]['end']):
+            return i
+        elif pos < bounds[i]['start']:# No use looking further
+            return -1
+
+    return -1
+
+
+def write_output(line,target=file_out):
+    '''This function takes the 2 dimensional array containing all the SNP
+    data. It contains an array of information on the feature and an array
+    for each strain for which SNPs are given.
+    Input: [[pos],[ref],[cells],[cells],etc]'''
+    target.write('\n'+str(line[0][0]))
+    for cell in line[1]:
+        target.write('\t'+str(cell))
+    for strain in line[2:]:
+        target.write('\t')
+        for cell in strain:
+            target.write('\t'+str(cell))
+    
+    target.flush()
+
+
+def new_codon_calc(ref_codon, new_base, pos_in_cod):
+    return str(ref_codon[0:pos_in_cod-1]+new_base+ref_codon[pos_in_cod:len(ref_codon)])
+
+
+def mut_type_check(ref_res, ref_codon, pos_in_gene, new_base, new_codon):
+    if str(new_codon).lower() == str(ref_codon).lower():
+        return ['','','','']
+    new_residue = Seq(new_codon).translate(table=transl_table)
+    if str(new_residue) == str(ref_res):
+        mut_type = 'synonymous'
+    elif (pos_in_gene / 3) < 1 and str(ref_codon).upper() in CodonTable.unambiguous_dna_by_id[transl_table].start_codons:# position 0,1 or 2 and SNP is in start codon;
+        if str(new_codon).upper() in CodonTable.unambiguous_dna_by_id[transl_table].start_codons: mut_type = 'nonsynonymous'
+        else: mut_type = 'nonstart'
+    elif str(new_residue) == '*': mut_type = 'nonsense'
+    elif str(ref_res) == '*': mut_type = 'nonstop'
+    else: mut_type = 'nonsynonymous'
+
+    return [mut_type,new_base,new_codon,new_residue]
+
+
+def codon_process(codon):
+    '''This function processes a codon. It loops through it 3 times,
+    once to determine which is the highest position mutated, once to
+    fill in the cells for the output file and once to output all lines.
+    Input: [empty,start_pos,[line1],[line2],[line3],strand]
+    It also uses global variable strain_nr'''
+    lastposition = [-1]*(strain_nr-1)
+    new_codons = ['']*(strain_nr-1)
+    if codon[-1] == -1:# Change codon position order for -1 features;
+        temp = codon [1:-1]
+        temp.reverse()
+        codon[1:-1] = temp
+    for i,line in enumerate(codon[1:-1],1):
+        if line == '': continue
+        for j,strain in enumerate(line[2:]):
+            if strain[1] in ['a','g','c','t']:
+                lastposition[j] = i
+                new_codons[j] = codon[i][1][8]
+
+    for i,line in enumerate(codon[1:-1],1):
+        if codon[-1] == -1: pos_in_cod = 4-i
+        else: pos_in_cod = i
+
+        if line == '': continue
+        for j,strain in enumerate(line[2:]):
+            if i == lastposition[j]: # Check for synonymous etc.;
+                new_codons[j] = new_codon_calc(new_codons[j],strain[1],pos_in_cod)
+                codon[i][j+2] = mut_type_check(line[1][9],line[1][8],codon[0],strain[1],new_codons[j])
+                straininfo[j][codon[i][j+2][0]] += 1# Counting;
+            elif strain[1] in ['a','g','c','t']:
+                codon[i][j+2] = ['MNP',strain[1],'','']
+                straininfo[j]['mnps'] += 1
+                new_codons[j] = new_codon_calc(new_codons[j],strain[1],pos_in_cod)
+            elif strain[0] == 'Allele missing': codon[i][j+2] = strain
+            else: codon[i][j+2] = ['']*4
+
+    for line in codon[1:-1]:
+        if line != '': write_output(line)
+
+def feature_props(feature):
+    properties = {'type':feature.type,'strand':feature.location._strand,
+                  'sequence':feature.extract(seq_record.seq),'pseudo': False,
+                  'locus_tag':'','gene_name':'','product':'',
+                  'start':int(feature.location._start.position),
+                'end':int(feature.location._end.position)}
+    if 'pseudo' in feature.qualifiers:
+        properties['pseudo'] = True
+        properties['type'] = 'pseudogene'
+        properties['pure_seq'] = properties['sequence']
+        if properties['strand'] == -1:
+            properties['sequence'] = seq_record.seq[feature.location._start.position:feature.location._end.position].reverse_complement()
+        else:
+            properties['sequence'] = seq_record.seq[feature.location._start.position:feature.location._end.position]
+        if feature.sub_features: properties['subfeats'] = feature.sub_features
+    if 'locus_tag' in feature.qualifiers: properties['locus_tag'] = feature.qualifiers['locus_tag'][0]
+    if 'gene' in feature.qualifiers: properties['gene_name']= feature.qualifiers['gene'][0]
+    if feature.type in ['tRNA','rRNA','CDS']: properties['product'] = feature.qualifiers['product'][0]
+
+    return properties
+    
+# Read embl/genbank file for information on sequence features;
+try:
+    seq_record = SeqIO.parse(file_ref, filetype_reference).next()
+except:
+    file_ref.close()
+    quit("Error reading "+sys.argv[2]+", please check file for errors.")
+file_ref.close()
+
+# Loop through genome features and save relevant properties;
+feats = []# Dictionary of properties;
+
+feature_types = {'intergenic':0,'gene':0,'pseudogene':0}
+feat_temp_store = ''
+for feature in seq_record.features:
+    # Check if gene is defined as other feature (e.g. CDS). Else, save info from 'gene';
+    if feat_temp_store != '':
+        if (feature.location._start.position == feat_temp_store.location._start.position and
+            feature.location._end.position == feat_temp_store.location._end.position):# Gene also defined as other feature;
+            feat_temp_store = ''
+        else:# Gene not also defined as CDS;
+            feats.append(feature_props(feat_temp_store))
+            feat_temp_store = ''
+    elif feature.type == 'gene':
+        feat_temp_store = feature
+
+    if not feature.type in ['source','gene','misc_feature']:
+        if not feature.type in feature_types and feature.type != 'CDS': feature_types[feature.type] = 0
+        feats.append(feature_props(feature))
+
+
+feat_props = sorted(feats, key=lambda cells:int(cells['start']))
+feat_boundaries = [{'start':item['start'],'end':item['end']} for item in feat_props]
+regions = region_calc(feat_boundaries,len(seq_record.seq))
+feat_overlap = overlap_calc(regions)
+
+reference_loaded = time.clock()
+
+# Create array of SNPs from input file for processing;
+lines = [line.split('\t') for line in file_snps if line.strip()]
+file_snps.close()
+# First line contains headers, extract number of strains etc;
+headers = lines[0]
+snp_table = sorted(lines[1:], key=lambda cells:int(cells[0]))
+
+snps_loaded = time.clock()
+
+# Print output file headers;
+headers[-1] = headers[-1].rstrip()# Remove newline character;
+strain_nr = len(headers)-1
+strains_found = 'Found '+str(strain_nr)+' strains: '+headers[1]+' (reference)'
+first_line = '\t'+headers[1]+'\t'*9
+second_line = 'Position\tFeature\tLocus tag\tGene\tProduct\tStart\tEnd\tStrand\tRef. base\tRef. codon\tRef. res.'
+straininfo = [0]*(len(headers[2:]))
+for i,strain in enumerate(headers[2:]):
+    straininfo[i] = {'snps':0,'mnps':0,'synonymous':0,'nonsynonymous':0,'nonstart':0,'nonstop':0,'nonsense':0}
+    straininfo[i].update(feature_types)
+    strains_found += ', '+strain
+    first_line += '\t\t'+strain+'\t'*3
+    second_line += '\t\tSNP type\tNew base\tNew codon\tNew res.'
+
+file_out.write(first_line+'\n'+second_line)
+file_out.flush()
+
+# Loop through SNPs from array and process them;
+props = {}# Properties of a feature;
+prev_snp = ''# Position of previous SNP;
+to_write = []# Information of current SNP;
+compl_bases = {'a':'t','t':'a','g':'c','c':'g'}
+firstsnp = True# First snp of region, or of codon in cases of 3 positions in codon mutated;
+prev_start=j=k=0
+overlap_snps = []
+codon = ['']*5# Array of codon positions. First item is position of first base of codon in the gene;
+
+for region in regions:
+    firstsnp = True
+    i = prev_start
+    while i < len(snp_table):# Loop through SNPs
+        snp_entry = snp_table[i]
+        if not str(snp_entry[0]).isdigit():# Not a valid line, skip;
+            i += 1
+            continue
+
+        pos = int(snp_entry[0])-1
+        if pos < region[0]:# Not inside region yet;
+            i += 1
+            continue
+        elif firstsnp and pos < region[1]:
+            prev_start = i
+        elif pos >= region[1]:# End of region, process and next;
+            if not firstsnp and codon != ['','','','','']:
+                codon_process(codon)
+            break
+
+        # Documentation of SNPs in feature overlaps;
+        while j < len(feat_overlap)-1 and pos > feat_overlap[j][1]: j += 1
+        k = j
+        while k < len(feat_overlap) and pos >= feat_overlap[k][0]:
+            if pos < feat_overlap[k][1]:
+                if feat_overlap[k][4][0] == 0:
+                    feat_overlap[k][4][0] = pos
+                feat_overlap[k][4][1] = pos
+            k += 1
+
+
+        snp_entry[-1] = snp_entry[-1].rstrip()# Remove newline character at end of line;
+
+	# Prevent crash upon encounter nonstandard base character;
+	if snp_entry[1] not in ['a','g','c','t']:# Ref base
+	    i += 1
+	    continue
+	for m,base in enumerate(snp_entry[2:],2):
+	    if base.lower() not in ['a','g','c','t']:
+		snp_entry[m] = ''
+	# Crash prevented
+
+        mnp=in_feat=False
+        snp_feat = region[2]
+        ref_base = snp_entry[1]
+
+        to_write = [[pos+1]]
+
+        # Output feature properties and reference situation;
+        if snp_feat == -1:
+            codon = ['']*5
+            to_write.append(['intergenic','','','','','','',ref_base.upper(),'',''])
+        elif feat_props[snp_feat]['type'] not in ['CDS','gene','pseudogene']:# In feature, but non-coding;
+            codon = ['']*5
+            props = feat_props[snp_feat]
+            if props['strand'] == -1: ref_base = (compl_bases[snp_entry[1].lower()])
+            else: ref_base = snp_entry[1]
+            to_write.append([props['type'],props['locus_tag'],props['gene_name'],
+                             props['product'],props['start']+1,props['end'],
+                             '',ref_base.upper(),'',''])
+        else:# in CDS/gene feature, check codon etc;
+            props = feat_props[snp_feat]
+            sequence = props['sequence']
+            if props['strand'] == -1:
+                pos_in_gene = props['end'] - pos - 1# Python counting
+                ref_base = (compl_bases[snp_entry[1].lower()])
+            else:
+                pos_in_gene = pos - props['start']# Python counting
+                ref_base = snp_entry[1]
+
+            in_feat = True
+            if props['pseudo'] and 'subfeats' in props:# Pseudogene that needs special attention;
+                in_feat = False
+                subfeat_boundaries = [{'start':item.location._start.position,'end':item.location._end.position}
+                                      for item in props['subfeats']]
+                snp_subfeat = match_feature(subfeat_boundaries,pos)
+                if snp_subfeat != -1:
+                    in_feat = True
+                    pos_in_gene -= non_coding_calc({'start':props['start'],'subfeats':props['subfeats'],
+                                                'pseudo':True,'strand':props['strand']},pos)
+                    sequence = props['pure_seq']
+
+            if not in_feat:# In pseudogene non-coding region;
+                codon = ['']*5
+                to_write.append(['non coding',props['locus_tag'],props['gene_name'],props['product'],
+                             props['start']+1,props['end'],props['strand'],ref_base.upper(),
+                             '',''])
+            else:# In coding region;
+                pos_in_cod = (pos_in_gene+1)%3
+                if pos_in_cod == 0: pos_in_cod = 3# Remainder of division 0 means 3rd place in codon;
+
+                old_codon = sequence[pos_in_gene-pos_in_cod+1:pos_in_gene-pos_in_cod+4].upper()
+                old_residue = old_codon.translate(table=transl_table)
+                to_write.append([props['type'],props['locus_tag'],props['gene_name'],props['product'],
+                                 props['start']+1,props['end'],props['strand'],ref_base.upper(),
+                                 old_codon,old_residue])
+
+            if in_feat and not firstsnp and (pos >= prev_snp):# Check if snp is in same codon as previous snp. Position check for overlapping features;
+                if props['strand'] == 1 and (pos - prev_snp + 1) < pos_in_cod:# Same codon (Positive strand);
+                    mnp = True
+                elif props['strand'] == -1 and (pos  - prev_snp + 1) <= (3 - pos_in_cod):# Same codon (negative strand);
+                    mnp = True
+
+            # Process previous codon if not MNP;
+            if in_feat and not mnp:
+                if not firstsnp:
+                    codon_process(codon)
+                codon = [pos_in_gene-pos_in_cod+1,'','','',props['strand']]
+
+
+        for l, snp in enumerate(snp_entry[2:]):# Loop through SNPs/strains;
+
+            snp = snp.lower()
+            if snp == '':# Empty cell;
+                to_write.append(['','','',''])
+                continue
+
+            if snp == '-': # Feature not present in this strain;
+                to_write.append(['Allele missing','','',''])
+                continue
+
+            if snp_feat == -1:# Intergenic;
+                if snp == ref_base.lower():
+                    to_write.append(['']*4)
+                else:
+                    to_write.append(['',snp,'',''])
+                    straininfo[l]['intergenic'] += 1
+                    straininfo[l]['snps'] += 1
+                continue
+
+            if props['strand'] == -1:
+                snp = compl_bases[snp]
+
+            if snp == ref_base.lower():
+                to_write.append(['']*4)
+            else:
+                to_write.append(['',snp,'',''])
+                straininfo[l]['snps'] += 1
+                if props['type'] != 'CDS':
+                    straininfo[l][props['type']] += 1
+
+
+
+        if props['type'] in ['CDS','gene','pseudogene'] and in_feat:
+            codon[pos_in_cod] = to_write
+        else:
+            write_output(to_write)
+
+        if firstsnp: firstsnp = False           
+        prev_snp = pos+1
+        i += 1
+
+
+if codon != ['','','','','']: codon_process(codon)
+
+file_out.close()
+
+end = time.clock()
+
+file_summary.write("\n")
+file_summary.write(intro_message)
+file_summary.write('\n'+strains_found+'.\n')
+
+file_summary.write("\nFinished annotation. Total time: %s s\n\n" % round(end-start,1))
+
+
+file_overlap.write('SNP start\tSNP end\tFeature 1\tLocus tag\tProduct\t\tFeature 2\tLocus tag\tProduct')
+for overlap in feat_overlap:
+    if overlap[4] != [0,0]:
+        overlap[4][0]+=1
+        overlap[4][1]+=1
+        if overlap[4][0] == overlap[4][1]: overlap[4][1] = ''
+        write_output([[str(overlap[4][0])],[str(overlap[4][1]),feat_props[overlap[2]]['type'],feat_props[overlap[2]]['locus_tag'],feat_props[overlap[2]]['product']],
+                        [feat_props[overlap[3]]['type'],feat_props[overlap[3]]['locus_tag'],feat_props[overlap[3]]['product']]],
+                        file_overlap)
+
+
+for i,strain in enumerate(headers[2:]):
+    file_summary.write("\n")
+    info = straininfo[i]
+    file_summary.write("+ Strain %s:\n" % strain)
+    file_summary.write("  %s SNPs found\n" % info['snps'])
+    file_summary.write("  Number of SNPs found CDS features: %s\n" % (info['mnps']+info['nonstart']+info['nonstop']+info['nonsense']+
+                                                     info['synonymous']+info['nonsynonymous']))
+    file_summary.write("  (of which in pseudogenes: %s)\n" % info['pseudogene'])
+    file_summary.write("  - MNPs:          %s\n" % info['mnps'])
+    file_summary.write("  - Synonymous:    %s\n" % info['synonymous'])
+    file_summary.write("  - Nonsynonymous: %s\n" % info['nonsynonymous'])
+    file_summary.write("  - Nonsense:      %s\n" % info['nonsense'])
+    file_summary.write("  - Nonstart:      %s\n" % info['nonstart'])
+    file_summary.write("  - Nonstop:       %s\n" % info['nonstop'])
+    file_summary.write("  Intergenic: %s\n" % info['intergenic'])
+
+    for typ in feature_types:
+        if typ not in  ['intergenic','pseudogene'] and info[typ] != 0:
+            file_summary.write("  %s: %s\n" % (typ,info[typ]))
+    file_summary.flush()
+
+file_overlap.close()
+file_summary.close()