# HG changeset patch
# User in_silico
# Date 1528819629 14400
# Node ID 2774c8433c4f303965d91d68e70c4d3627e361fa
# Parent 338d106513fd712db4f6edeb0a0d22a098f21d1b
Uploaded
diff -r 338d106513fd -r 2774c8433c4f cravat_convert/base_converter.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_convert/base_converter.py Tue Jun 12 12:07:09 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
diff -r 338d106513fd -r 2774c8433c4f cravat_convert/cravat_convert.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_convert/cravat_convert.py Tue Jun 12 12:07:09 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)
diff -r 338d106513fd -r 2774c8433c4f cravat_convert/cravat_convert.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_convert/cravat_convert.xml Tue Jun 12 12:07:09 2018 -0400
@@ -0,0 +1,20 @@
+
+ Converts a VCF format file to a Cravat format file
+ cravat_convert.py -i $input -o $output
+
+
+
+
+
+
+
+
+
+
+
+
+ Converts a VCF format file to a Cravat format file
+
+
+
+
diff -r 338d106513fd -r 2774c8433c4f cravat_convert/vcf_converter.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_convert/vcf_converter.py Tue Jun 12 12:07:09 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
diff -r 338d106513fd -r 2774c8433c4f cravat_submit/cravat_submit.py
--- a/cravat_submit/cravat_submit.py Tue Jun 12 12:06:54 2018 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,103 +0,0 @@
-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://staging.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://staging.cravat.us/CRAVAT/results/" + jobid + "/" + "Variant.Result.tsv", file_1)
-urllib.urlretrieve("http://staging.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
diff -r 338d106513fd -r 2774c8433c4f cravat_submit/cravat_submit.xml
--- a/cravat_submit/cravat_submit.xml Tue Jun 12 12:06:54 2018 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,34 +0,0 @@
-
- Submits, checks for, and retrieves data for cancer annotation
- cravat_submit.py $input $dropdown $output
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- This tool submits, checks for, and retrieves data for cancer annotation.
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