changeset 5:7048ccf0ff7b draft

Uploaded
author in_silico
date Tue, 12 Jun 2018 11:27:06 -0400
parents 93864b5201b6
children 4b0bee4d9a15
files cravat_convert/cravat_convert.py cravat_convert/cravat_convert.xml cravat_convert/vcf_converter.py
diffstat 3 files changed, 97 insertions(+), 243 deletions(-) [+]
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_convert/cravat_convert.py	Tue Jun 12 11:27:06 2018 -0400
@@ -0,0 +1,77 @@
+'''
+Convert a VCF format file to Cravat format file
+'''
+
+import os
+import argparse
+from vcf_converter import CravatConverter
+
+# File read/write configuration variables
+vcf_sep = '\t'
+cr_sep = '\t'
+cr_newline = '\n'
+
+# VCF Headers mapped to their index position in a row of VCF values
+vcf_mapping = {
+    'CHROM': 0,
+    'POS': 1,
+    'ID': 2,
+    'REF': 3,
+    'ALT': 4,
+    'QUAL': 5,
+    'FILTER': 6,
+    'INFO': 7,
+    'FORMAT': 8,
+    'NA00001': 9,
+    'NA00002': 10,
+    'NA00003': 11
+}
+
+
+def get_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--input',
+                            '-i',
+                            required = True,
+                            help='Input path to a VCF file for conversion',)
+    parser.add_argument('--output',
+                            '-o',
+                            default = os.path.join(os.getcwd(), "cravat_converted.txt"),
+                            help = 'Output path to write the cravat file to')
+    return parser.parse_args()
+
+
+def convert(in_path, out_path=None):
+    if not out_path:
+        base, _ = os.path.split(in_path)
+        out_path = os.path.join(base, "cravat_converted.txt")
+    
+    with open(in_path, 'r') as in_file, \
+    open(out_path, 'w') as out_file:
+
+        # cr_count will be used to generate the 'TR' field of the cravat rows (first header)
+        cr_count = 0
+        # VCF lines are always assumed to be '+' strand, as VCF doesn't specify that attribute
+        strand = '+'
+        # VCF converter. Adjusts position, reference, and alternate for Cravat formatting.
+        converter = CravatConverter()
+
+        for line in in_file:
+            if line.startswith("#"):
+                continue
+            line = line.strip().split(vcf_sep)
+            # row is dict of VCF headers mapped to corresponding values of this line
+            row = { header: line[index] for header, index in vcf_mapping.items() }
+            for alt in row["ALT"].split(","):
+                new_pos, new_ref, new_alt = converter.extract_vcf_variant(strand, row["POS"], row["REF"], alt)
+                new_pos, new_ref, new_alt = str(new_pos), str(new_ref), str(new_alt)
+                cr_line = cr_sep.join([
+                    'TR' + str(cr_count), row['CHROM'], new_pos, strand, new_ref, new_alt, row['ID']
+                ])
+                out_file.write(cr_line + cr_newline)
+                cr_count += 1
+
+
+if __name__ == "__main__":
+    cli_args = get_args()
+    convert(cli_args.input, cli_args.output)
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_convert/cravat_convert.xml	Tue Jun 12 11:27:06 2018 -0400
@@ -0,0 +1,20 @@
+<tool id="cravat_convert" name="CRAVAT Convert" version="1.0.0">
+    <description>Converts a VCF format file to a Cravat format file</description>
+    <command interpreter="python">cravat_convert.py -i $input -o $output</command>
+  
+    <inputs>
+        <param format="tabular" name="input" type="data" label="Source file"/>
+    </inputs>
+  
+    <outputs>
+        <data format="tabular" name="output" />
+    </outputs>
+
+    <!-- <tests></tests> -->
+
+    <help>
+        Converts a VCF format file to a Cravat format file
+    </help>
+
+</tool>
+
--- a/cravat_convert/vcf_converter.py	Tue Jun 12 11:26:47 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,243 +0,0 @@
-"""
-A module originally obtained from the cravat package. Modified to use in the vcf
-converter galaxy tool.
-
-
-Register of changes made (Chris Jacoby):
-    1) Changed imports as galaxy tool won't have access to complete cravat python package
-    2) Defined BadFormatError in BaseConverted file, as I didn't have the BadFormatError module
-"""
-
-from base_converter import BaseConverter, BadFormatError
-import re
-
-class CravatConverter(BaseConverter):
-    
-    def __init__(self):
-        self.format_name = 'vcf'
-        self.samples = []
-        self.var_counter = 0
-        self.addl_cols = [{'name':'phred',
-                           'title':'Phred',
-                           'type':'string'},
-                          {'name':'filter',
-                           'title':'VCF filter',
-                           'type':'string'},
-                          {'name':'zygosity',
-                           'title':'Zygosity',
-                           'type':'string'},
-                          {'name':'alt_reads',
-                           'title':'Alternate reads',
-                           'type':'int'},
-                          {'name':'tot_reads',
-                           'title':'Total reads',
-                           'type':'int'},
-                          {'name':'af',
-                           'title':'Variant allele frequency',
-                           'type':'float'}]
-    
-    def check_format(self, f): 
-        return f.readline().startswith('##fileformat=VCF')
-    
-    def setup(self, f):
-        
-        vcf_line_no = 0
-        for line in f:
-            vcf_line_no += 1
-            if len(line) < 6:
-                continue
-            if line[:6] == '#CHROM':
-                toks = re.split('\s+', line.rstrip())
-                if len(toks) > 8:
-                    self.samples = toks[9:]
-                break
-    
-    def convert_line(self, l):
-        if l.startswith('#'): return None
-        self.var_counter += 1
-        toks = l.strip('\r\n').split('\t')
-        all_wdicts = []
-        if len(toks) < 8:
-            raise BadFormatError('Wrong VCF format')
-        [chrom, pos, tag, ref, alts, qual, filter, info] = toks[:8]
-        if tag == '':
-            raise BadFormatError('ID column is blank')
-        elif tag == '.':
-            tag = 'VAR' + str(self.var_counter)
-        if chrom[:3] != 'chr':
-            chrom = 'chr' + chrom
-        alts = alts.split(',')
-        len_alts = len(alts)
-        if len(toks) == 8:
-            for altno in range(len_alts):
-                wdict = None
-                alt = alts[altno]
-                newpos, newref, newalt = self.extract_vcf_variant('+', pos, ref, alt)
-                wdict = {'tags':tag,
-                         'chrom':chrom,
-                         'pos':newpos,
-                         'ref_base':newref,
-                         'alt_base':newalt,
-                         'sample_id':'no_sample',
-                         'phred': qual,
-                         'filter': filter}
-                all_wdicts.append(wdict)
-        elif len(toks) > 8:
-            sample_datas = toks[9:]
-            genotype_fields = {}
-            genotype_field_no = 0
-            for genotype_field in toks[8].split(':'):
-                genotype_fields[genotype_field] = genotype_field_no
-                genotype_field_no += 1
-            if not ('GT' in genotype_fields):
-                raise BadFormatError('No GT Field')
-            gt_field_no = genotype_fields['GT']
-            for sample_no in range(len(sample_datas)):
-                sample = self.samples[sample_no]
-                sample_data = sample_datas[sample_no].split(':')
-                gts = {}
-                for gt in sample_data[gt_field_no].replace('/', '|').split('|'):
-                    if gt == '.':
-                        continue
-                    else:
-                        gts[int(gt)] = True
-                for gt in sorted(gts.keys()):
-                    wdict = None
-                    if gt == 0:
-                        continue
-                    else:
-                        alt = alts[gt - 1]
-                        newpos, newref, newalt = self.extract_vcf_variant('+', pos, ref, alt)
-                        zyg = self.homo_hetro(sample_data[gt_field_no])
-                        depth, alt_reads, af = self.extract_read_info(sample_data, gt, gts, genotype_fields)
-                            
-                        wdict = {'tags':tag,
-                                 'chrom':chrom,
-                                 'pos':newpos,
-                                 'ref_base':newref,
-                                 'alt_base':newalt,
-                                 'sample_id':sample,
-                                 'phred': qual,
-                                 'filter': filter,
-                                 'zygosity': zyg,
-                                 'tot_reads': depth,
-                                 'alt_reads': alt_reads,
-                                 'af': af,                                
-                                 }
-                        all_wdicts.append(wdict)
-        return all_wdicts
- 
-    #The vcf genotype string has a call for each allele separated by '\' or '/'
-    #If the call is the same for all allels, return 'hom' otherwise 'het'
-    def homo_hetro(self, gt_str):
-        if '.' in gt_str:
-            return '';
-        
-        gts = gt_str.strip().replace('/', '|').split('|')
-        for gt in gts:
-            if gt != gts[0]:
-                return 'het'
-        return 'hom'            
-                        
-    #Extract read depth, allele count, and allele frequency from optional VCR information
-    def extract_read_info (self, sample_data, gt, gts, genotype_fields): 
-        depth = ''
-        alt_reads = ''
-        ref_reads = ''
-        af = ''
-        
-        #AD contains 2 values usually ref count and alt count unless there are 
-        #multiple alts then it will have alt 1 then alt 2.
-        if 'AD' in genotype_fields and genotype_fields['AD'] <= len(sample_data): 
-            if 0 in gts.keys():
-                #if part of the genotype is reference, then AD will have #ref reads, #alt reads
-                ref_reads = sample_data[genotype_fields['AD']].split(',')[0]
-                alt_reads = sample_data[genotype_fields['AD']].split(',')[1]
-            elif gt == max(gts.keys()):    
-                #if geontype has multiple alt bases, then AD will have #alt1 reads, #alt2 reads
-                alt_reads = sample_data[genotype_fields['AD']].split(',')[1]
-            else:
-                alt_reads = sample_data[genotype_fields['AD']].split(',')[0]                            
-                             
-        if 'DP' in genotype_fields and genotype_fields['DP'] <= len(sample_data): 
-            depth = sample_data[genotype_fields['DP']] 
-        elif alt_reads != '' and ref_reads != '':
-            #if DP is not present but we have alt and ref reads count, dp = ref+alt
-            depth = int(alt_reads) + int(ref_reads)   
-
-        if 'AF' in genotype_fields and genotype_fields['AF'] <= len(sample_data):
-            af = float(sample_data[genotype_fields['AF']] )
-        elif depth != '' and alt_reads != '':
-            #if AF not specified, calc it from alt and ref reads
-            af = float(alt_reads) / float(depth)
- 
-        return depth, alt_reads, af
-            
-    def extract_vcf_variant (self, strand, pos, ref, alt):
-
-        reflen = len(ref)
-        altlen = len(alt)
-        
-        # Returns without change if same single nucleotide for ref and alt. 
-        if reflen == 1 and altlen == 1 and ref == alt:
-            return pos, ref, alt
-        
-        # Trimming from the start and then the end of the sequence 
-        # where the sequences overlap with the same nucleotides
-        new_ref2, new_alt2, new_pos = \
-            self.trimming_vcf_input(ref, alt, pos, strand)
-                
-        if new_ref2 == '':
-            new_ref2 = '-'
-        if new_alt2 == '':
-            new_alt2 = '-'
-        
-        return new_pos, new_ref2, new_alt2
-    
-    # This function looks at the ref and alt sequences and removes 
-    # where the overlapping sequences contain the same nucleotide.
-    # This trims from the end first but does not remove the first nucleotide 
-    # because based on the format of VCF input the 
-    # first nucleotide of the ref and alt sequence occur 
-    # at the position specified.
-    #     End removed first, not the first nucleotide
-    #     Front removed and position changed
-    def trimming_vcf_input(self, ref, alt, pos, strand):
-        pos = int(pos)
-        reflen = len(ref)
-        altlen = len(alt)
-        minlen = min(reflen, altlen)
-        new_ref = ref
-        new_alt = alt
-        new_pos = pos
-        # Trims from the end. Except don't remove the first nucleotide. 
-        # 1:6530968 CTCA -> GTCTCA becomes C -> GTC.
-        for nt_pos in range(0, minlen - 1): 
-            if ref[reflen - nt_pos - 1] == alt[altlen - nt_pos - 1]:
-                new_ref = ref[:reflen - nt_pos - 1]
-                new_alt = alt[:altlen - nt_pos - 1]
-            else:
-                break    
-        new_ref_len = len(new_ref)
-        new_alt_len = len(new_alt)
-        minlen = min(new_ref_len, new_alt_len)
-        new_ref2 = new_ref
-        new_alt2 = new_alt
-        # Trims from the start. 1:6530968 G -> GT becomes 1:6530969 - -> T.
-        for nt_pos in range(0, minlen):
-            if new_ref[nt_pos] == new_alt[nt_pos]:
-                if strand == '+':
-                    new_pos += 1
-                elif strand == '-':
-                    new_pos -= 1
-                new_ref2 = new_ref[nt_pos + 1:]
-                new_alt2 = new_alt[nt_pos + 1:]
-            else:
-                new_ref2 = new_ref[nt_pos:]
-                new_alt2 = new_alt[nt_pos:]
-                break  
-        return new_ref2, new_alt2, new_pos
-
-
-if __name__ == "__main__":
-    c = CravatConverter()
\ No newline at end of file