changeset 9:6b607ebcd674 draft

Uploaded

--- a/cravat_convert/base_converter.py	Tue Jun 12 12:06:11 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	Tue Jun 12 12:06:11 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,77 +0,0 @@
-'''
-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)

--- a/cravat_convert/cravat_convert.xml	Tue Jun 12 12:06:11 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	Tue Jun 12 12:06:11 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	Tue Jun 12 12:06:28 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://staging.cravat.us/CRAVAT/rest/service/submit', files={'inputfile':open(input_filename)}, data={'email':'[e-mail]', '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

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_submit/cravat_submit.xml	Tue Jun 12 12:06:28 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>