| Previous changeset 4:953e716d7837 (2018-06-12) Next changeset 6:3439857aa913 (2018-06-12) |
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cravat_submit/cravat_submit.py cravat_submit/cravat_submit.xml cravat_submit/vcf_converter.py |
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| diff -r 953e716d7837 -r 2ccaad5c7c01 cravat_submit/cravat_submit.py --- a/cravat_submit/cravat_submit.py Tue Jun 12 11:54:00 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| @@ -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 |
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| diff -r 953e716d7837 -r 2ccaad5c7c01 cravat_submit/cravat_submit.xml --- a/cravat_submit/cravat_submit.xml Tue Jun 12 11:54:00 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| @@ -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> |
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| diff -r 953e716d7837 -r 2ccaad5c7c01 cravat_submit/vcf_converter.py --- a/cravat_submit/vcf_converter.py Tue Jun 12 11:54:00 2018 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 |
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| b'@@ -1,243 +0,0 @@\n-"""\r\n-A module originally obtained from the cravat package. Modified to use in the vcf\r\n-converter galaxy tool.\r\n-\r\n-\r\n-Register of changes made (Chris Jacoby):\r\n- 1) Changed imports as galaxy tool won\'t have access to complete cravat python package\r\n- 2) Defined BadFormatError in BaseConverted file, as I didn\'t have the BadFormatError module\r\n-"""\r\n-\r\n-from base_converter import BaseConverter, BadFormatError\r\n-import re\r\n-\r\n-class CravatConverter(BaseConverter):\r\n- \r\n- def __init__(self):\r\n- self.format_name = \'vcf\'\r\n- self.samples = []\r\n- self.var_counter = 0\r\n- self.addl_cols = [{\'name\':\'phred\',\r\n- \'title\':\'Phred\',\r\n- \'type\':\'string\'},\r\n- {\'name\':\'filter\',\r\n- \'title\':\'VCF filter\',\r\n- \'type\':\'string\'},\r\n- {\'name\':\'zygosity\',\r\n- \'title\':\'Zygosity\',\r\n- \'type\':\'string\'},\r\n- {\'name\':\'alt_reads\',\r\n- \'title\':\'Alternate reads\',\r\n- \'type\':\'int\'},\r\n- {\'name\':\'tot_reads\',\r\n- \'title\':\'Total reads\',\r\n- \'type\':\'int\'},\r\n- {\'name\':\'af\',\r\n- \'title\':\'Variant allele frequency\',\r\n- \'type\':\'float\'}]\r\n- \r\n- def check_format(self, f): \r\n- return f.readline().startswith(\'##fileformat=VCF\')\r\n- \r\n- def setup(self, f):\r\n- \r\n- vcf_line_no = 0\r\n- for line in f:\r\n- vcf_line_no += 1\r\n- if len(line) < 6:\r\n- continue\r\n- if line[:6] == \'#CHROM\':\r\n- toks = re.split(\'\\s+\', line.rstrip())\r\n- if len(toks) > 8:\r\n- self.samples = toks[9:]\r\n- break\r\n- \r\n- def convert_line(self, l):\r\n- if l.startswith(\'#\'): return None\r\n- self.var_counter += 1\r\n- toks = l.strip(\'\\r\\n\').split(\'\\t\')\r\n- all_wdicts = []\r\n- if len(toks) < 8:\r\n- raise BadFormatError(\'Wrong VCF format\')\r\n- [chrom, pos, tag, ref, alts, qual, filter, info] = toks[:8]\r\n- if tag == \'\':\r\n- raise BadFormatError(\'ID column is blank\')\r\n- elif tag == \'.\':\r\n- tag = \'VAR\' + str(self.var_counter)\r\n- if chrom[:3] != \'chr\':\r\n- chrom = \'chr\' + chrom\r\n- alts = alts.split(\',\')\r\n- len_alts = len(alts)\r\n- if len(toks) == 8:\r\n- for altno in range(len_alts):\r\n- wdict = None\r\n- alt = alts[altno]\r\n- newpos, newref, newalt = self.extract_vcf_variant(\'+\', pos, ref, alt)\r\n- wdict = {\'tags\':tag,\r\n- \'chrom\':chrom,\r\n- \'pos\':newpos,\r\n- \'ref_base\':newref,\r\n- \'alt_base\':newalt,\r\n- \'sample_id\':\'no_sample\',\r\n- \'phred\': qual,\r\n- \'filter\': filter}\r\n- all_wdicts.append(wdict)\r\n- elif len(toks) > 8:\r\n- sample_datas = toks[9:]\r\n- genotype_fields = {}\r\n- genotype_field_no = 0\r\n- for genotype_field in toks[8].split(\':\'):\r\n- genotype_fields[genotype_field] = genotype_field_no\r\n- genotype_field_no += 1\r\n- if not (\'GT\' in genotype_fields):\r\n- raise BadFormatError(\'No GT Field\')\r\n- gt_field_no = genotype_fields[\'GT\']\r\n- for sample_no in range(len(sample_datas)):\r\n- sample = self.samples[sample_no]\r\n- sample_data = sample_datas[sample_no].split(\':\')\r\n- gts = {}\r\n- for gt in sample_data[gt_field_no].replace(\'/\', \'|\').split(\'|\'):\r\n- '..b'\r\n- ref_reads = sample_data[genotype_fields[\'AD\']].split(\',\')[0]\r\n- alt_reads = sample_data[genotype_fields[\'AD\']].split(\',\')[1]\r\n- elif gt == max(gts.keys()): \r\n- #if geontype has multiple alt bases, then AD will have #alt1 reads, #alt2 reads\r\n- alt_reads = sample_data[genotype_fields[\'AD\']].split(\',\')[1]\r\n- else:\r\n- alt_reads = sample_data[genotype_fields[\'AD\']].split(\',\')[0] \r\n- \r\n- if \'DP\' in genotype_fields and genotype_fields[\'DP\'] <= len(sample_data): \r\n- depth = sample_data[genotype_fields[\'DP\']] \r\n- elif alt_reads != \'\' and ref_reads != \'\':\r\n- #if DP is not present but we have alt and ref reads count, dp = ref+alt\r\n- depth = int(alt_reads) + int(ref_reads) \r\n-\r\n- if \'AF\' in genotype_fields and genotype_fields[\'AF\'] <= len(sample_data):\r\n- af = float(sample_data[genotype_fields[\'AF\']] )\r\n- elif depth != \'\' and alt_reads != \'\':\r\n- #if AF not specified, calc it from alt and ref reads\r\n- af = float(alt_reads) / float(depth)\r\n- \r\n- return depth, alt_reads, af\r\n- \r\n- def extract_vcf_variant (self, strand, pos, ref, alt):\r\n-\r\n- reflen = len(ref)\r\n- altlen = len(alt)\r\n- \r\n- # Returns without change if same single nucleotide for ref and alt. \r\n- if reflen == 1 and altlen == 1 and ref == alt:\r\n- return pos, ref, alt\r\n- \r\n- # Trimming from the start and then the end of the sequence \r\n- # where the sequences overlap with the same nucleotides\r\n- new_ref2, new_alt2, new_pos = \\\r\n- self.trimming_vcf_input(ref, alt, pos, strand)\r\n- \r\n- if new_ref2 == \'\':\r\n- new_ref2 = \'-\'\r\n- if new_alt2 == \'\':\r\n- new_alt2 = \'-\'\r\n- \r\n- return new_pos, new_ref2, new_alt2\r\n- \r\n- # This function looks at the ref and alt sequences and removes \r\n- # where the overlapping sequences contain the same nucleotide.\r\n- # This trims from the end first but does not remove the first nucleotide \r\n- # because based on the format of VCF input the \r\n- # first nucleotide of the ref and alt sequence occur \r\n- # at the position specified.\r\n- # End removed first, not the first nucleotide\r\n- # Front removed and position changed\r\n- def trimming_vcf_input(self, ref, alt, pos, strand):\r\n- pos = int(pos)\r\n- reflen = len(ref)\r\n- altlen = len(alt)\r\n- minlen = min(reflen, altlen)\r\n- new_ref = ref\r\n- new_alt = alt\r\n- new_pos = pos\r\n- # Trims from the end. Except don\'t remove the first nucleotide. \r\n- # 1:6530968 CTCA -> GTCTCA becomes C -> GTC.\r\n- for nt_pos in range(0, minlen - 1): \r\n- if ref[reflen - nt_pos - 1] == alt[altlen - nt_pos - 1]:\r\n- new_ref = ref[:reflen - nt_pos - 1]\r\n- new_alt = alt[:altlen - nt_pos - 1]\r\n- else:\r\n- break \r\n- new_ref_len = len(new_ref)\r\n- new_alt_len = len(new_alt)\r\n- minlen = min(new_ref_len, new_alt_len)\r\n- new_ref2 = new_ref\r\n- new_alt2 = new_alt\r\n- # Trims from the start. 1:6530968 G -> GT becomes 1:6530969 - -> T.\r\n- for nt_pos in range(0, minlen):\r\n- if new_ref[nt_pos] == new_alt[nt_pos]:\r\n- if strand == \'+\':\r\n- new_pos += 1\r\n- elif strand == \'-\':\r\n- new_pos -= 1\r\n- new_ref2 = new_ref[nt_pos + 1:]\r\n- new_alt2 = new_alt[nt_pos + 1:]\r\n- else:\r\n- new_ref2 = new_ref[nt_pos:]\r\n- new_alt2 = new_alt[nt_pos:]\r\n- break \r\n- return new_ref2, new_alt2, new_pos\r\n-\r\n-\r\n-if __name__ == "__main__":\r\n- c = CravatConverter()\n\\ No newline at end of file\n' |