changeset 24:e46db72f5b74 draft

Uploaded
author in_silico
date Wed, 18 Jul 2018 10:25:27 -0400
parents f8703ba30180
children f447e525d3b2
files cravat_annotate/cravat_annotate.py cravat_annotate/cravat_annotate.xml 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
diffstat 8 files changed, 365 insertions(+), 153 deletions(-) [+]
line wrap: on
line diff
--- a/cravat_annotate/cravat_annotate.py	Wed Jul 18 10:25:17 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,128 +0,0 @@
-import requests
-import json
-import sys
-import re
-import argparse
-from __future__ import print_function
-
-
-# The endpoint that CravatQuerys are submitted to
-endpoint = 'http://www.cravat.us/CRAVAT/rest/service/query'
-
-
-# newline and delimiter values used in the output file
-delimiter = "\t"
-newline = "\n"
-
-
-# Defualt indices for intepretting a cravat file's row of data in to a CravatQuery
-cr_mapping = {
-	'chromosome': 1,
-	'position': 2,
-	'strand': 3,
-	'reference': 4,
-	'alternate': 5
-}
-
-
-# The neccessary attributes neeeded to submit a query.
-query_keys = [
-	'chromosome', 'position', 'strand', 'reference', 'alternate'
-]
-
-
-# Expected response keys from server. Ordered in list so that galaxy output has uniform column ordering run-to-run.
-# If cravat server returns additional keys, they are appended to and included in output.
-ordered_keys = [
-	"Chromosome", "Position", "Strand", "Reference base(s)", "Alternate base(s)",
-	"HUGO symbol", "S.O. transcript", "Sequence ontology protein change", "Sequence ontology",
-	"S.O. all transcripts", "gnomAD AF", "gnomAD AF (African)", "gnomAD AF (Amrican)",
-	"gnomAD AF (Ashkenazi Jewish)", "gnomAD AF (East Asian)", "gnomAD AF (Finnish)",
-	"gnomAD AF (Non-Finnish European)", "gnomAD AF (Other)", "gnomAD AF (South Asian)",
-	"1000 Genomes AF", "ESP6500 AF (average)", "ESP6500 AF (European American)",
-	"ESP6500 AF (African American)", "COSMIC transcript", "COSMIC protein change", 
-	"COSMIC variant count [exact nucleotide change]", "cosmic_site_nt", "CGL driver class",
-	"TARGET", "dbSNP", "cgc_role", "cgc_inheritance", "cgc_tumor_type_somatic",
-	"cgc_tumor_type_germline", "ClinVar", "ClinVar disease identifier", "ClinVar XRef",
-	"GWAS Phenotype (GRASP)", "GWAS PMID (GRASP)", "Protein 3D variant"
-]
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-    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')
-    return parser.parse_args()
-
-
-def format_chromosome(chrom):
-	""" : Ensure chromosome entry is propely formatted for use as querying attribute. """
-	if chrom[0:3] == 'chr':
-		return chrom
-	return 'chr' + str(chrom)
-
-
-def get_query_string(row):
-	""" : From a row dict, return a query string for the Cravat server.
-		: The row dict is cravat headeres associated to their values of that row.
-	"""
-	return '_'.join([ row['chromosome'], row['position'], row['strand'], row['reference'], row['alternate'] ])
-
-
-def query(in_path, out_path):
-	""" : From a Cravat the file at in_path, query each line on the Cravat server.
-		: Write the response values to file at out_path.
-	"""
-	with open(in_path, 'r') as in_file, \
-	open(out_path, 'w') as out_file:
-		for line in in_file:
-			try:
-				line = line.strip().split('\t')
-				# row is dict of cravat col headers assioted values in this line
-				row = { header: line[index] for header, index in cr_mapping.items() }
-				row['chromosome'] = format_chromosome(row['chromosome'])
-				query_string = get_query_string(row)
-				call = requests.get(endpoint, params={ 'mutation': query_string })
-				if call.status_code != 200 or call.text == "":
-					raise requests.RequestException('Bad server response for query="{}". Respone code: "{}", Response Text: "{}"'
-						.format(query_string, call.status_code, call.text))
-				json_response = json.loads(call.text)
-				# See if server returned additional json key-vals not expected in ordered_keys
-				for key in json_response:
-					if key not in ordered_keys:
-						ordered_keys.append(key)
-				# Write key in order of ordered_keys to standardize order of output columns
-				wrote = False
-				for key in ordered_keys:
-					if key in json_response:
-						val = json_response[key]
-					else:
-						val = None
-					# Standardize format for  numeric values
-					try:
-						val = float(val)
-						val = format(val, ".4f")
-					except:
-						pass
-					if wrote:
-						out_file.write(delimiter)
-					out_file.write(str(val))
-					wrote = True
-				out_file.write(newline)		
-			except Exception as e:
-				print(e, file=sys.stderr)
-				continue
-
-
-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") 
-	query(cli_args.input, cli_args.output)
--- a/cravat_annotate/cravat_annotate.xml	Wed Jul 18 10:25:17 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,25 +0,0 @@
-<tool id="cravat_query" name="CRAVAT Query" version="1.0.0">
-    <description>Queries CRAVAT for cancer annotation</description>
-  <command interpreter="python">cravat_annotate.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>
-    <test>
-      <param name="input" value="input_call.txt"/>
-      <output name="output" file="Galaxy23-[CRAVAT_Query_on_data_22].tabular"/>
-    </test>
-  </tests>
-
-  <help>
-    This tool queries CRAVAT for cancer annotation.
-  </help>
-
-</tool>
-
Binary file cravat_convert/__pycache__/base_converter.cpython-36.pyc has changed
Binary file cravat_convert/__pycache__/vcf_converter.cpython-36.pyc has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat_convert/base_converter.py	Wed Jul 18 10:25:27 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	Wed Jul 18 10:25:27 2018 -0400
@@ -0,0 +1,80 @@
+import os
+import argparse
+from vcf_converter import CravatConverter
+from __future__ import print_function
+
+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	Wed Jul 18 10:25:27 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	Wed Jul 18 10:25:27 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