Mercurial > repos > in_silico > cravat_vcf_convert
changeset 17:bea3b63f4b5d draft
Uploaded
| author | in_silico |
|---|---|
| date | Wed, 18 Jul 2018 09:41:08 -0400 |
| parents | a9944bb8a9b8 |
| children | cde9e74d9fdf |
| files | cravat_convert/__pycache__/base_converter.cpython-36.pyc cravat_convert/__pycache__/vcf_converter.cpython-36.pyc cravat_convert/base_converter.py cravat_convert/cravat_convert.py cravat_convert/cravat_convert.xml cravat_convert/vcf_converter.py cravat_submit/cravat_submit.py cravat_submit/cravat_submit.xml |
| diffstat | 8 files changed, 137 insertions(+), 371 deletions(-) [+] |
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--- a/cravat_convert/base_converter.py Wed Jun 27 17:54:42 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,22 +0,0 @@ -class BaseConverter(object): - def __init__(self): - self.format_name = None - def check_format(self,*args,**kwargs): - err_msg = 'Converter for %s format has no method check_format' %\ - self.format_name - raise NotImplementedError(err_msg) - def setup(self,*args,**kwargs): - err_msg = 'Converter for %s format has no method setup' %\ - self.format_name - raise NotImplementedError(err_msg) - def convert_line(self,*args,**kwargs): - err_msg = 'Converter for %s format has no method convert_line' %\ - self.format_name - raise NotImplementedError(err_msg) - - -class BadFormatError(Exception): - def __init__(self, message, errors=None): - super(BadFormatError, self).__init__(message) - # Support for custom error codes, if added later - self.errors = errors \ No newline at end of file
--- a/cravat_convert/cravat_convert.py Wed Jun 27 17:54:42 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,86 +0,0 @@ -''' -Convert a VCF format file to Cravat format file -''' - -import os -import argparse -from vcf_converter import CravatConverter -### -# import ipdb - - -def get_vcf_mapping(): - """ : VCF Headers mapped to their index position in a row of VCF values. - : These are only the mandatory columns, per the VCF spec. - """ - return { - 'CHROM': 0, - 'POS': 1, - 'ID': 2, - 'REF': 3, - 'ALT': 4, - 'QUAL': 5, - 'FILTER': 6, - 'INFO': 7 - } - - -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 = None, - help = 'Output path to write the cravat file to') - return parser.parse_args() - - -def convert(in_path, out_path=None, cr_sep='\t', cr_newline='\n'): - """ : Convert a VCF file to a Cravat file. - : Arguments: - : in_path: <str> path to input vcf file - : out_path: <str> path to output cravat file. Will defualt to cravat_converted.txt in the input directory. - : cr_sep: <str> the value delimiter for the output cravat file. Default value of '\\t'. - : out_newline: <str> the newline delimiter in the output cravat file. Default of '\\n' - """ - 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() - # A dictionary of mandatory vcf headers mapped to their row indices - vcf_mapping = get_vcf_mapping() - - for line in in_file: - if line.startswith("#"): - continue - line = line.strip().split() - # 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() - if cli_args.output == None: - base, _ = os.path.split(cli_args.input) - cli_args.output = os.path.join(base, "cravat_converted.txt") - convert(in_path = cli_args.input, out_path = cli_args.output)
--- a/cravat_convert/cravat_convert.xml Wed Jun 27 17:54:42 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,20 +0,0 @@ -<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 Wed Jun 27 17:54:42 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
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cravat_submit/cravat_submit.py Wed Jul 18 09:41:08 2018 -0400 @@ -0,0 +1,103 @@ +import requests +import json +import time +import urllib +import sys +import csv + +input_filename = sys.argv[1] +input_select_bar = sys.argv[2] +output_filename = sys.argv[3] + +# HACK: Input args corrections. +if input_select_bar == "None": + # The server represents an analyses of None as ""; however, submitting a blank string on command line throws off arg position + input_select_bar = "" + # The server represents the "Vest and Chasm" analyses as "VEST;CHASM; however, galaxy converts the semi-colon to an 'X'. Switch it back. +elif input_select_bar == "VESTXCHASM": + input_select_bar = "VEST;CHASM" + +write_header = True + +#plugs in params to given URL +submit = requests.post('http://cravat.us/CRAVAT/rest/service/submit', files={'inputfile':open(input_filename)}, data={'email':'znylund@insilico.us.com', 'analyses': input_select_bar}) +#,'analysis':input_select_bar,'functionalannotation': "on"}) +#Makes the data a json dictionary, takes out only the job ID +jobid = json.loads(submit.text)['jobid'] +#out_file.write(jobid) +submitted = json.loads(submit.text)['status'] +#out_file.write('\t' + submitted) + +#loops until we find a status equal to Success, then breaks +while True: + check = requests.get('http://staging.cravat.us/CRAVAT/rest/service/status', params={'jobid': jobid}) + status = json.loads(check.text)['status'] + resultfileurl = json.loads(check.text)['resultfileurl'] + #out_file.write(str(status) + ', ') + if status == 'Success': + #out_file.write('\t' + resultfileurl) + break + else: + time.sleep(2) + +#out_file.write('\n') + +#creates three files +file_1 = time.strftime("%H:%M") + '_Z_Variant_Result.tsv' +file_2 = time.strftime("%H:%M") + '_Z_Additional_Details.tsv' +file_3 = time.strftime("%H:%M") + 'Combined_Variant_Results.tsv' + + +#Download the two results +urllib.urlretrieve("http://cravat.us/CRAVAT/results/" + jobid + "/" + "Variant.Result.tsv", file_1) +urllib.urlretrieve("http://cravat.us/CRAVAT/results/" + jobid + "/" + "Variant_Additional_Details.Result.tsv", file_2) + +headers = [] +duplicates = [] + +#opens the Variant Result file and the Variant Additional Details file as csv readers, then opens the output file (galaxy) as a writer +with open(file_1) as tsvin_1, open(file_2) as tsvin_2, open(output_filename, 'wb') as tsvout: + tsvreader_1 = csv.reader(tsvin_1, delimiter='\t') + tsvreader_2 = csv.reader(tsvin_2, delimiter='\t') + tsvout = csv.writer(tsvout, delimiter='\t') + +#loops through each row in the Variant Additional Details file + for row in tsvreader_2: + #sets row_2 equal to the same row in Variant Result file + row_2 = tsvreader_1.next() + #checks if row is empty or if the first term contains '#' + if row == [] or row[0][0] == '#': + continue + #checks if the row begins with input line + if row[0] == 'Input line': + #Goes through each value in the headers list in VAD + for value in row: + #Adds each value into headers + headers.append(value) + #Loops through the Keys in VR + for value in row_2: + #Checks if the value is already in headers + if value in headers: + continue + #else adds the header to headers + else: + headers.append(value) + + print headers + tsvout.writerow(headers) + + + else: + + cells = [] + #Goes through each value in the next list + for value in row: + #adds it to cells + cells.append(value) + #Goes through each value from the VR file after position 11 (After it is done repeating from VAD file) + for value in row_2[11:]: + #adds in the rest of the values to cells + cells.append(value) + + print cells + tsvout.writerow(cells) \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cravat_submit/cravat_submit.xml Wed Jul 18 09:41:08 2018 -0400 @@ -0,0 +1,34 @@ +<tool id="cravat_submit" name="CRAVAT Submit, Check, and Retrieve" version="0.1.0"> + <description>Submits, checks for, and retrieves data for cancer annotation</description> + <command interpreter="python">cravat_submit.py $input $dropdown $output</command> + + + <inputs> + + <param format="tabular" name="input" type="data" label="Source file"> </param> + <param format="tabular" name="dropdown" type="select" label="Analysis Program"> + <option value="None">None</option> + <option value="VEST">VEST</option> + <option value="CHASM">CHASM</option> + <option value="VEST;CHASM">VEST and CHASM</option> + </param> + + + </inputs> + + <outputs> + <data format="tabular" name="output" /> + </outputs> + + <tests> + <test> + <param name="input" value="fa_gc_content_input.fa"/> + <output name="out_file1" file="fa_gc_content_output.txt"/> + </test> + </tests> + + <help> + This tool submits, checks for, and retrieves data for cancer annotation. + </help> + +</tool>