Mercurial > repos > in_silico > cravat_score_and_annotate
changeset 14:45b91fdd18ce draft
Uploaded
| author | in_silico |
|---|---|
| date | Mon, 30 Jul 2018 13:31:57 -0400 |
| parents | 2c9208fe16a0 |
| children | 0835042eb731 |
| 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, 365 insertions(+), 204 deletions(-) [+] |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cravat_convert/base_converter.py Mon Jul 30 13:31:57 2018 -0400 @@ -0,0 +1,22 @@ +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
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cravat_convert/cravat_convert.py Mon Jul 30 13:31:57 2018 -0400 @@ -0,0 +1,80 @@ +from __future__ import print_function +import os +import argparse +from vcf_converter import CravatConverter + +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)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cravat_convert/cravat_convert.xml Mon Jul 30 13:31:57 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> +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cravat_convert/vcf_converter.py Mon Jul 30 13:31:57 2018 -0400 @@ -0,0 +1,243 @@ +""" +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
--- a/cravat_submit/cravat_submit.py Mon Jul 30 13:22:46 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,170 +0,0 @@ -from __future__ import print_function -import requests -import json -import time -from urllib.request import urlretrieve -import sys -import csv -import argparse - -""" -Tool's email: -usernmae: cravatgalaxy@gmail.com -password: chicken_quesadilla -""" - -email = 'cravatgalaxy@gmail.com' - -class CravatSubmissionException(Exception): - def __init__(self, message): - super(CravatSubmissionException, self).__init__(message) - -class CravatSubmission(object): - - def get_cmd_args(self, argv): - parser = argparse.ArgumentParser() - parser.add_argument('path', - help="Path to python module") - parser.add_argument('--input', - '-i', - required = True, - help='Input path to a cravat file for querying',) - parser.add_argument('--output', - '-o', - default = None, - help = 'Output path to write results from query') - parser.add_argument('--analysis', - '-a', - required=True, - help = "Cravat analysis. Should be 'VEST', 'CHASM', 'NONE', or 'VEST;CHASM'") - return parser.parse_args(argv) - - def is_valid_analysis(self, analysis): - """: Test if analysis is a recognized value""" - analyses = ["VEST", "CHASM", "VEST;CHASM", ""] - return analysis in analyses - - def is_skippable(self, s): - """: Test if a line (str or list/tuple) is skippable, a.k.a. a header or blank line""" - if not isinstance(s, str): - raise CravatSubmissionException("is_skippable accepts a string") - skippable = s == "" \ - or s[0] == "#" \ - or s.startswith('"#For more information on CRAVAT') \ - or s.isspace() - return skippable - - def parse(self, s, sep='\t'): - """: Convert string line to an array of values""" - return s.strip().split(sep) - - def unparse(self, array, sep='\t', newline='\n'): - """: Convert an array of values to a writable string line""" - return sep.join([str(i) for i in array]) + newline - - def get_headers(self, path, pattern='Input line', sep='\t'): - """: Get the headers from a Results/Details file obtained from by a finished Cravat submission""" - with open(path, 'r') as f: - for line in f: - if line.startswith(pattern): - return self.parse(line) - return None - - def create_index(self, path, prop='Input line'): - """ - : Create an index of seek/tell positions in file associated to a line value. Used to record - : the location of lines betwen two files that are associated with each other without reading entire - : files into memory. - """ - headers = self.get_headers(path) - if prop not in headers: - raise CravatSubmissionException("Index retrievel property not found in headers") - prop_loc = headers.index(prop) - index = {} - with open(path, 'r') as f: - pos = 0 - line = f.readline() - while line != "": - if not self.is_skippable(line): - parsed = self.parse(line) - if not parsed == headers: - index[parsed[prop_loc]] = pos - pos = f.tell() - line = f.readline() - return index - - def get_header_val_dict(self, headers, vals): - """: Associate an array of header keys to an array of values.""" - return { header:val for (header, val) in zip(headers, vals) } - - def write_results(self, results_path, details_path, out_path, write_headers=True): - """ - : Using the paths to the Results and Details file from a Cravat Sumbission, - : write the output file. - """ - results_headers = self.get_headers(results_path) - details_headers = self.get_headers(details_path) - if results_headers == None \ - or details_headers == None: - raise CravatSubmissionException("Unable to intepret headers in Results or Details submission files") - headers = results_headers - headers.extend(filter(lambda x: x not in headers, details_headers)) - results_index = self.create_index(results_path) - details_index = self.create_index(details_path) - with open(results_path, 'r') as results_file, \ - open(details_path, 'r') as details_file, \ - open(out_path, 'w') as out_file: - if write_headers: - out_file.write(self.unparse(headers)) - for line_id, file_pos in results_index.items(): - results_file.seek(file_pos) - results_vals = self.parse(results_file.readline()) - results_dict = self.get_header_val_dict(results_headers, results_vals) - if line_id in details_index: - details_file.seek(details_index[line_id]) - details_vals = self.parse(details_file.readline()) - details_dict = self.get_header_val_dict(details_headers, details_vals) - # On a repeated entry, the Details value will overwrite Results value - results_dict.update(details_dict) - line = [ results_dict.get(header, 'None') for header in headers ] - out_file.write(self.unparse(line)) - - def submit(self, in_path, analysis): - """: Make a POST request to submit a job to production CRAVAT server.""" - if not self.is_valid_analysis(analysis): - raise ValueError("Did not get valid analyses.") - # Create post request to submit job to CRAVAT production server - submit = requests.post('http://cravat.us/CRAVAT/rest/service/submit', - files={'inputfile' : open(in_path)}, - data={'email' : email, - 'analyses' : analysis}) - # Check job run status in loop until status is 'Success' - jobid = json.loads(submit.text)['jobid'] - while True: - check = requests.get('http://cravat.us/CRAVAT/rest/service/status', params={'jobid': jobid}) - status = json.loads(check.text)['status'] - print(status) - if status == 'Success': - break - else: - time.sleep(2) - # Download completed job results to local files - timestamp = time.strftime("%Y-%m-%d_%H-%M-%S_") - results_path = 'Z_Variant_Result' + timestamp + '.tsv' - details_path = 'Z_Additional_Details' + timestamp + '.tsv' - urlretrieve("http://cravat.us/CRAVAT/results/" + jobid + "/" + "Variant.Result.tsv", - filename=results_path) - urlretrieve("http://cravat.us/CRAVAT/results/" + jobid + "/" + "Variant_Additional_Details.Result.tsv", - filename=details_path) - return results_path, details_path - -if __name__ == "__main__": - submission = CravatSubmission() - cmd_args = submission.get_cmd_args(sys.argv) - # Galaxy converts semi-colons to X's. Switch it back - analysis = cmd_args.analysis - if analysis == "VESTXCHASM": - analysis = "VEST;CHASM" - results_path, details_path = submission.submit(cmd_args.input, analysis) - #submission.write_results('Results_test.tsv', 'Details_test.tsv', 'Out_test.tsv') - submission.write_results(results_path, details_path, cmd_args.output) \ No newline at end of file
--- a/cravat_submit/cravat_submit.xml Mon Jul 30 13:22:46 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,34 +0,0 @@ -<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>