changeset 1:2c7bcc1219fc draft

Updated cravatool to version 1.0 with updated formatting and new CRAVAT target URL.
author galaxyp
date Thu, 16 Aug 2018 12:27:35 -0400
parents 83181dabeb90
children f3027b8f28bd
files ._cravatp_submit.py ._cravatp_submit.xml cravat_submit.py cravat_submit.xml cravatp_submit.py cravatp_submit.xml test-data/._variant.tsv test-data/Freebayes.vcf test-data/Freebayes_one-variant.vcf test-data/Freebayes_special-cases.vcf test-data/Freebayes_two-variants.vcf test-data/MCF7_proBed.bed test-data/[PepPointer].bed test-data/[VCF-BEDintersect__on_data_65_and_data_6].vcf test-data/error.tsv test-data/gene.tsv test-data/noncoding.tsv test-data/results/intersected_vcf.vcf test-data/variant.tsv test-results/Additional_Details.tsv test-results/Gene_Level_Analysis.tsv test-results/Input_Errors.Result.tsv test-results/Variant_Non-coding.Result.tsv test-results/Variant_Result.tsv test-results/combined_variants.tsv
diffstat 25 files changed, 3375 insertions(+), 986 deletions(-) [+]
line wrap: on
line diff
Binary file ._cravatp_submit.py has changed
Binary file ._cravatp_submit.xml has changed
--- a/cravat_submit.py	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,287 +0,0 @@
-import requests
-import json
-import time
-import urllib
-import sys
-import csv
-import re
-import math
-from difflib import SequenceMatcher
-from xml.etree import ElementTree as ET
-import sqlite3
-
-try:
-    input_filename = sys.argv[1]
-    input_select_bar = sys.argv[2]
-    GRCh_build = sys.argv[3]
-    probed_filename = sys.argv[4]
-    output_filename = sys.argv[5]
-    file_3 = sys.argv[6]
-    file_4 = sys.argv[7]
-    file_5 = sys.argv[8]
-except:
-    # Filenames for testing.
-    input_filename = 'test-data/[VCF-BEDintersect__on_data_65_and_data_6].vcf'
-    probed_filename = 'test-data/[PepPointer].bed'
-    input_select_bar = 'VEST'
-    GRCh_build = 'GRCh38'
-    output_filename = 'combined_variants.tsv'
-    file_3 = 'test-results/Gene_Level_Analysis.tsv'
-    file_4 = 'test-results/Variant_Non-coding.Result.tsv'
-    file_5 = 'test-results/Input_Errors.Result.tsv'
-    matches_filename = 'matches.tsv'
-
-def getSequence(transcript_id):
-    server = 'http://rest.ensembl.org'
-    ext = '/sequence/id/' + transcript_id + '?content-type=text/x-seqxml%2Bxml;multiple_sequences=1;type=protein'
-    req = requests.get(server+ext, headers={ "Content-Type" : "text/plain"})
-    
-    if not req.ok:
-        return None
-    
-    root = ET.fromstring(req.content)
-    for child in root.iter('AAseq'):
-        return child.text
-
-
-write_header = True
-
-GRCh37hg19 = 'off'
-if GRCh_build == 'GRCh37':
-    GRCh37hg19 = 'on'
-
-#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, 'hg19': GRCh37hg19})
-
-#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)
-
-input_file = open(input_filename)
-
-# Loads the proBED file as a list. 
-if (probed_filename != 'None'):
-    proBED = []
-    with open(probed_filename) as tsvin:
-        tsvreader = csv.reader(tsvin, delimiter='\t')
-        for i, row in enumerate(tsvreader):
-            proBED.append(row)
-  
-#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 = 'Variant_Result.tsv'
-file_2 = 'Additional_Details.tsv'
-#file_3 = time.strftime("%H:%M") + 'Combined_Variant_Results.tsv'
-
-#Downloads the tabular 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)
-urllib.urlretrieve("http://staging.cravat.us/CRAVAT/results/" + jobid + "/" + "Gene_Level_Analysis.Result.tsv", file_3)
-urllib.urlretrieve("http://staging.cravat.us/CRAVAT/results/" + jobid + "/" + "Variant_Non-coding.Result.tsv", file_4)
-urllib.urlretrieve("http://staging.cravat.us/CRAVAT/results/" + jobid + "/" + "Input_Errors.Result.tsv", file_5)
-
-#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_2 = csv.reader(tsvin_2, delimiter='\t')        
-    tsvout = csv.writer(tsvout, delimiter='\t')
-
-    headers = []
-    duplicate_indices = []
-    n = 12 #Index for proteogenomic column start
-    reg_seq_change = re.compile('([A-Z]+)(\d+)([A-Z]+)')
-    SOtranscripts = re.compile('([A-Z]+[\d\.]+):([A-Z]+\d+[A-Z]+)')
-    pep_muts = {}
-    pep_map = {}
-    rows = []
-
-    for row in tsvreader_2:
-        if row != [] and row[0][0] != '#':
-        #checks if the row begins with input line
-            if row[0] == 'Input line':
-                vad_headers = row
-            else:
-                # Initially screens through the output Variant Additional Details to catch mutations on same peptide region
-                genchrom = row[vad_headers.index('Chromosome')]
-                genpos = int(row[vad_headers.index('Position')])
-                aa_change = row[vad_headers.index('Protein sequence change')]
-                input_line = row[vad_headers.index('Input line')]
-                
-                for peptide in proBED:
-                    pepseq = peptide[3]
-                    pepchrom = peptide[0]
-                    pepposA = int(peptide[1])
-                    pepposB = int(peptide[2])
-                    if genchrom == pepchrom and pepposA <= genpos and genpos <= pepposB:
-                        strand = row[vad_headers.index('Strand')]
-                        transcript_strand = row[vad_headers.index('S.O. transcript strand')]
-
-                        # Calculates the position of the variant amino acid(s) on peptide
-                        if transcript_strand == strand:                               
-                            aa_peppos = int(math.ceil((genpos - pepposA)/3.0) - 1)
-                        if strand == '-' or transcript_strand == '-' or aa_peppos >= len(pepseq):
-                            aa_peppos = int(math.floor((pepposB - genpos)/3.0))
-                        if pepseq in pep_muts:
-                            if aa_change not in pep_muts[pepseq]:
-                                pep_muts[pepseq][aa_change] = [aa_peppos]
-                            else:
-                                if aa_peppos not in pep_muts[pepseq][aa_change]:
-                                    pep_muts[pepseq][aa_change].append(aa_peppos)
-                        else:
-                            pep_muts[pepseq] = {aa_change : [aa_peppos]}
-                        # Stores the intersect information by mapping Input Line (CRAVAT output) to peptide sequence.
-                        if input_line in pep_map:
-                            if pepseq not in pep_map[input_line]:
-                                pep_map[input_line].append(pepseq)
-                        else:
-                            pep_map[input_line] = [pepseq]
-
-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')
-
-    headers = []
-            
-    #loops through each row in the Variant Additional Details (VAD) file
-    for row in tsvreader_2:
-        
-        #sets row_2 equal to the same row in Variant Result (VR) file
-        row_2 = tsvreader_1.next()
-        #checks if row is empty or if the first term contains '#'
-        if row == [] or row[0][0] == '#':
-            tsvout.writerow(row)
-        else:
-            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 i,value in enumerate(row_2):
-                    #Checks if the value is already in headers
-                    if value in headers:
-                        duplicate_indices.append(i)
-                        continue
-                    #else adds the header to headers
-                    else:
-                        headers.append(value)
-                #Adds appropriate headers when proteomic input is supplied
-                if (probed_filename != 'None'):
-                    headers.insert(n, 'Variant peptide')
-                    headers.insert(n, 'Reference peptide')
-                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 i,value in enumerate(row_2):
-                    #adds in the rest of the values to cells
-                    if i not in duplicate_indices:
-                        # Skips the initial 11 columns and the VEST p-value (already in VR file)
-                        cells.append(value)
-
-                # Verifies the peptides intersected previously through sequences obtained from Ensembl's API
-                if (probed_filename != 'None'):
-                    cells.insert(n,'')
-                    cells.insert(n,'')
-                    input_line = cells[headers.index('Input line')]
-                    if input_line in pep_map:
-                        pepseq = pep_map[input_line][0]
-                        aa_changes = pep_muts[pepseq]
-                        transcript_id = cells[headers.index('S.O. transcript')]
-                        ref_fullseq = getSequence(transcript_id)
-                        # Checks the other S.O. transcripts if the primary S.O. transcript has no sequence available
-                        if not ref_fullseq:
-                            transcripts = cells[headers.index('S.O. all transcripts')]
-                            for transcript in transcripts.split(','):
-                                if transcript:
-                                    mat = SOtranscripts.search(transcript)
-                                    ref_fullseq = getSequence(mat.group(1))
-                                    if ref_fullseq:
-                                        aa_changes = {mat.group(2): [aa_changes.values()[0][0]]}
-                                        break
-                        # Resubmits the previous transcripts without extensions if all S.O. transcripts fail to provide a sequence
-                        if not ref_fullseq:
-                            transcripts = cells[headers.index('S.O. all transcripts')]
-                            for transcript in transcripts.split(','):
-                                if transcript:
-                                    mat = SOtranscripts.search(transcript)
-                                    ref_fullseq = getSequence(mat.group(1).split('.')[0])
-                                    if ref_fullseq:
-                                        aa_changes = {mat.group(2): [aa_changes.values()[0][0]]}
-                                        break
-                        if ref_fullseq:
-                            # Sorts the amino acid changes
-                            positions = {}
-                            for aa_change in aa_changes:
-                                m = reg_seq_change.search(aa_change)
-                                aa_protpos = int(m.group(2))
-                                aa_peppos = aa_changes[aa_change][0]
-                                aa_startpos = aa_protpos - aa_peppos - 1
-                                if aa_startpos in positions:
-                                    positions[aa_startpos].append(aa_change)
-                                else:
-                                    positions[aa_startpos] = [aa_change]
-                            # Goes through the sorted categories to mutate the Ensembl peptide (uses proBED peptide as a reference)
-                            for pep_protpos in positions:
-                                ref_seq = ref_fullseq[pep_protpos:pep_protpos+len(pepseq)]
-                                muts = positions[pep_protpos]
-                                options = []
-                                mut_seq = ref_seq
-                                for mut in muts:
-                                    m = reg_seq_change.search(mut)
-                                    ref_aa = m.group(1)
-                                    mut_pos = int(m.group(2))
-                                    alt_aa = m.group(3)
-                                    pep_mutpos = mut_pos - pep_protpos - 1
-                                    if ref_seq[pep_mutpos] == ref_aa and (pepseq[pep_mutpos] == alt_aa or pepseq[pep_mutpos] == ref_aa):
-                                        if pepseq[pep_mutpos] == ref_aa:
-                                            mut_seq = mut_seq[:pep_mutpos] + ref_aa + mut_seq[pep_mutpos+1:]
-                                        else:
-                                            mut_seq = mut_seq[:pep_mutpos] + alt_aa + mut_seq[pep_mutpos+1:]
-                                    else:
-                                        break
-                                # Adds the mutated peptide and reference peptide if mutated correctly
-                                if pepseq == mut_seq:
-                                    cells[n+1] = pepseq
-                                    cells[n] = ref_seq
-                #print  cells
-                tsvout.writerow(cells)
-
-
-
-            
-    
-
-#a = 'col1\tcol2\tcol3'
-#header_list = a.split('\t')
-
-#loop through the two results, when you first hit header you print out the headers in tabular form
-#Print out each header only once
-#Combine both headers into one output file
-#loop through the rest of the data and assign each value to its assigned header
-#combine this all into one output file
-
-
-
-
-
--- a/cravat_submit.xml	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,44 +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 $GRCh $psm $Variant $Gene $Noncoding $Error</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</option>
-      <option value="VEST">VEST</option>
-      <option value="CHASM">CHASM</option>
-      <option value="VEST;CHASM">VEST and CHASM</option>
-    </param>
-    <param format="tabular" name="GRCh" type="select" label="Genome Reference Consortium Human Build (GRCh)">
-      <option value="GRCh38">GRCh38/hg38</option>
-      <option value="GRCh37">GRCh37/hg19</option>
-    </param>
-    <param format="tabular" name="psm" type="data" optional="true" label="ProBED File(Optional)"> </param>
-    
-    
-  </inputs>
-  
-  <outputs>
-      <collection name="collection" type="list" label="CRAVAT Results: ${on_string} using ${dropdown}">
-        <data format="cravat" label="CRAVAT: Gene Level Annotation Report" name="Gene" />
-        <data format="cravat" label="CRAVAT: Variant Report" name="Variant" />
-        <data format="cravat" label="CRAVAT: Non-coding Variant Report" name="Noncoding" />
-        <data format="cravat" label="CRAVAT: Errors" name="Error" />
-      </collection>
-  </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 from the CRAVAT platform at cravat.us.
-  </help>
-
-</tool>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravatp_submit.py	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,390 @@
+# -*- coding: utf-8 -*-
+#
+# Author: Ray W. Sajulga
+# 
+#
+
+import requests # pipenv requests
+import json
+import time
+import urllib
+import sys
+import csv
+import re
+import math
+import argparse
+from xml.etree import ElementTree as ET
+from zipfile import ZipFile
+try: #Python 3
+    from urllib.request import urlopen
+except ImportError: #Python 2
+    from urllib2 import urlopen
+from io import BytesIO
+
+# initializes blank parameters
+chasm_classifier = ''
+probed_filename = None
+intersected_only = False
+vcf_output = None
+analysis_type = None
+
+# # Testing Command
+# python cravatp_submit.py test-data/Freebayes_two-variants.vcf GRCh38
+# test-data/variant.tsv test-data/gene.tsv test-data/noncoding.tsv
+# test-data/error.tsv CHASM -—classifier Breast -—proBED
+# test-data/MCF7_proBed.bed
+parser = argparse.ArgumentParser()
+parser.add_argument('cravatInput',help='The filename of the input '
+                                       'CRAVAT-formatted tabular file '
+                                       '(e.g., VCF)')
+parser.add_argument('GRCh', help='The name of the human reference '
+                                 'genome used for annotation: '
+                                 'GRCh38/hg38 or GRCh37/hg19')
+parser.add_argument('variant', help='The filename of the output '
+                                     'variant file')
+parser.add_argument('gene', help='The filename of the output gene '
+                                 'variant report')
+parser.add_argument('noncoding', help='The filename of the output '
+                                       'non-coding variant report')
+parser.add_argument('error', help='The filename of the output error '
+                                  'file')
+parser.add_argument('analysis', help='The machine-learning algorithm '
+                                     'used for CRAVAT annotation (VEST'
+                                     ' and/or CHASM)')
+parser.add_argument('--classifier', help='The cancer classifier for the'
+                                         ' CHASM algorithm')
+parser.add_argument('--proBED', help='The filename of the proBED file '
+                                     'containing peptides with genomic '
+                                     'coordinates')
+parser.add_argument('--intersectOnly', help='Specifies whether to '
+                                            'analyze only variants '
+                                            'intersected between the '
+                                            'CRAVAT input and proBED '
+                                            'file')
+parser.add_argument('--vcfOutput', help='The output filename of the '
+                                        'intersected VCF file')
+
+# assigns parsed arguments to appropriate variables
+args = parser.parse_args()
+input_filename = args.cravatInput
+GRCh_build = args.GRCh
+output_filename = args.variant
+file_3 = args.gene
+file_4 = args.noncoding
+file_5 = args.error
+if args.analysis != 'None':
+    analysis_type = args.analysis
+if args.classifier:
+    chasm_classifier = args.classifier
+if args.proBED:
+    probed_filename = args.proBED
+if args.intersectOnly:
+    intersected_only = args.intersectOnly    
+if args.vcfOutput:
+    vcf_output = args.vcfOutput
+
+if analysis_type and '+' in analysis_type:
+    analysis_type = 'CHASM;VEST'
+
+# obtains the transcript's protein sequence using Ensembl API
+def getSequence(transcript_id):
+    server = 'http://rest.ensembl.org'
+    ext = ('/sequence/id/' + transcript_id 
+           + '?content-type=text/x-seqxml%2Bxml;'
+             'multiple_sequences=1;type=protein')
+    req = requests.get(server+ext,
+                       headers={ "Content-Type" : "text/plain"})
+    
+    if not req.ok:
+        return None
+    
+    root = ET.fromstring(req.content)
+    for child in root.iter('AAseq'):
+        return child.text
+
+# parses the proBED file as a list. 
+def loadProBED():
+    proBED = []
+    with open(probed_filename) as tsvin:
+        tsvreader = csv.reader(tsvin, delimiter='\t')
+        for i, row in enumerate(tsvreader):
+            proBED.append(row)
+    return proBED
+
+write_header = True
+
+
+# Creates an VCF file that only contains variants that overlap with the
+# proteogenomic input (proBED) file if the user specifies that they want
+# to only include intersected variants or if they want to receive the
+# intersected VCF as well.
+if probed_filename and (vcf_output or intersected_only == 'true'):
+    proBED = loadProBED()
+    if not vcf_output:
+        vcf_output = 'intersected_input.vcf'
+    with open(input_filename) as tsvin, open(vcf_output, 'wb') as tsvout:
+        tsvreader = csv.reader(tsvin, delimiter='\t')        
+        tsvout = csv.writer(tsvout, delimiter='\t', escapechar=' ',
+                            quoting=csv.QUOTE_NONE)
+
+        for row in tsvreader:
+            if row == [] or row[0][0] == '#':
+                tsvout.writerow(row)
+            else:
+                genchrom = row[0]
+                genpos = int(row[1])
+
+                for peptide in proBED:
+                    pepchrom = peptide[0]
+                    pepposA = int(peptide[1])
+                    pepposB = int(peptide[2])
+                    if (genchrom == pepchrom and
+                        pepposA <= genpos and
+                                   genpos <= pepposB):
+                        tsvout.writerow(row)
+                        break
+if intersected_only == 'true':
+    input_filename = vcf_output
+
+# sets up the parameters for submission to the CRAVAT API
+parameters = {'email':'rsajulga@umn.edu',
+              'hg19': 'on' if GRCh_build == 'GRCh37' else 'off',
+              'functionalannotation': 'on',
+              'tsvreport' : 'on',
+              'mupitinput' : 'on'}
+if analysis_type:
+    parameters['analyses'] = analysis_type
+if chasm_classifier:
+    parameters['chasmclassifier'] = chasm_classifier
+    
+# plugs in params to given URL
+submit = requests.post('http://www.cravat.us/CRAVAT/rest/service/submit',
+                       files = {'inputfile':open(input_filename)},
+                       data = parameters)
+
+# makes the data a json dictionary; takes out only the job ID
+jobid = json.loads(submit.text)['jobid']
+
+# loops until we find a status equal to Success, then breaks
+while True:
+    check = requests.get(
+                'http://www.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)
+
+# obtains the zipfile created by CRAVAT and loads the variants and VAD
+# file for processing
+r = requests.get(resultfileurl, stream=True)
+url = urlopen(resultfileurl)
+zipfile = ZipFile(BytesIO(r.content))
+variants = zipfile.open(jobid + '/Variant.Result.tsv').readlines()
+vad = zipfile.open(jobid + '/Variant_Additional_Details.Result.tsv').readlines()
+
+# reads and writes the gene, noncoding, and error files
+open(file_3, 'wb').write(zipfile.read(jobid + '/Gene_Level_Analysis.Result.tsv'))
+open(file_4, 'wb').write(zipfile.read(jobid + '/Variant_Non-coding.Result.tsv'))
+open(file_5, 'wb').write(zipfile.read(jobid + '/Input_Errors.Result.tsv'))
+
+
+
+if probed_filename and not vcf_output:
+    proBED = loadProBED()
+
+if probed_filename:
+    with open(output_filename, 'w') as tsvout:
+        tsvout = csv.writer(tsvout,
+                            delimiter='\t',
+                            escapechar=' ',
+                            quoting=csv.QUOTE_NONE)
+        n = 11 #Index for proteogenomic column start
+        reg_seq_change = re.compile('([A-Z]+)(\d+)([A-Z]+)')
+        SOtranscripts = re.compile('([A-Z]+[\d\.]+):([A-Z]+\d+[A-Z]+)')
+        pep_muts = {}
+        pep_map = {}
+        rows = []
+        for row in vad:
+            row = row.decode().split('\t')
+            row[-1] = row[-1].replace('\n','')
+            if row and row[0] and not row[0].startswith('#'):
+                # checks if the row begins with input line
+                if row[0].startswith('Input line'):
+                    vad_headers = row
+                    
+                else:
+                    # Initially screens through the output Variant
+                    # Additional Details to catch mutations on
+                    # same peptide region
+                    genchrom = row[vad_headers.index('Chromosome')]
+                    genpos = int(row[vad_headers.index('Position')])
+                    aa_change = row[vad_headers.index('Protein sequence change')]
+                    input_line = row[vad_headers.index('Input line')]
+                    
+                    for peptide in proBED:
+                        pepseq = peptide[3]
+                        pepchrom = peptide[0]
+                        pepposA = int(peptide[1])
+                        pepposB = int(peptide[2])
+                        if genchrom == pepchrom and pepposA <= genpos and genpos <= pepposB:
+                            strand = row[vad_headers.index('Strand')]
+                            transcript_strand = row[vad_headers.index('S.O. transcript strand')]
+
+                            # Calculates the position of the variant
+                            # amino acid(s) on peptide
+                            if transcript_strand == strand:                               
+                                aa_peppos = int(math.ceil((genpos - pepposA)/3.0) - 1)
+                            if (strand == '-' or transcript_strand == '-'
+                                    or aa_peppos >= len(pepseq)):
+                                aa_peppos = int(math.floor((pepposB - genpos)/3.0))
+                            if pepseq in pep_muts:
+                                if aa_change not in pep_muts[pepseq]:
+                                    pep_muts[pepseq][aa_change] = [aa_peppos]
+                                else:
+                                    if aa_peppos not in pep_muts[pepseq][aa_change]:
+                                        pep_muts[pepseq][aa_change].append(aa_peppos)
+                            else:
+                                pep_muts[pepseq] = {aa_change : [aa_peppos]}
+                            # Stores the intersect information by mapping
+                            # Input Line (CRAVAT output) to peptide sequence.
+                            if input_line in pep_map:
+                                if pepseq not in pep_map[input_line]:
+                                    pep_map[input_line].append(pepseq)
+                            else:
+                                pep_map[input_line] = [pepseq]
+                            # TODO: Need to obtain strand information as
+                            # well i.e., positive (+) or negative (-)
+
+                            
+with open(output_filename, 'w') as tsvout:
+    tsvout = csv.writer(tsvout, delimiter='\t', escapechar='',
+                        quoting=csv.QUOTE_NONE)
+    headers = []
+    duplicate_indices = []
+            
+    # loops through each row in the Variant Additional Details (VAD) file
+    for x, row in enumerate(variants):
+        row = row.decode().split('\t')
+        row[-1] = row[-1].replace('\n','')
+        # sets row_2 equal to the same row in Variant Result (VR) file
+        row_2 = vad[x].decode().split('\t')
+        row_2[-1] = row_2[-1].replace('\n','')
+        
+        # checks if row is empty or if the first term contains '#'
+        if not row or not row[0] or row[0].startswith('#'):
+            if row[0]:
+                tsvout.writerow(row)
+        else:
+            if row[0].startswith('Input line'):
+                # goes through each value in the headers list in VAD
+                headers = row
+                # loops through the Keys in VR
+                for i,value in enumerate(row_2):
+                    #Checks if the value is already in headers
+                    if value in headers:
+                        duplicate_indices.append(i)
+                        continue
+                    #else adds the header to headers
+                    else:
+                        headers.append(value)
+                # adds appropriate headers when proteomic input is supplied
+                if probed_filename:
+                    headers.insert(n, 'Variant peptide')
+                    headers.insert(n, 'Reference peptide')
+                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 i,value in enumerate(row_2):
+                    # adds in the rest of the values to cells
+                    if i not in duplicate_indices:
+                        # Skips the initial 11 columns and the
+                        # VEST p-value (already in VR file)
+                        cells.append(value)
+
+                # Verifies the peptides intersected previously through
+                # sequences obtained from Ensembl's API
+                if probed_filename:
+                    cells.insert(n,'')
+                    cells.insert(n,'')
+                    input_line = cells[headers.index('Input line')]
+                    if input_line in pep_map:
+                        pepseq = pep_map[input_line][0]
+                        aa_changes = pep_muts[pepseq]
+                        transcript_id = cells[headers.index('S.O. transcript')]
+                        ref_fullseq = getSequence(transcript_id)
+                        # Checks the other S.O. transcripts if the primary
+                        # S.O. transcript has no sequence available
+                        if not ref_fullseq:
+                            transcripts = cells[headers.index('S.O. all transcripts')]
+                            for transcript in transcripts.split(','):
+                                if transcript:
+                                    mat = SOtranscripts.search(transcript)
+                                    ref_fullseq = getSequence(mat.group(1))
+                                    if ref_fullseq:
+                                        aa_changes = {mat.group(2): [aa_changes.values()[0][0]]}
+                                        break
+                        # Resubmits the previous transcripts without
+                        # extensions if all S.O. transcripts fail to
+                        # provide a sequence
+                        if not ref_fullseq:
+                            transcripts = cells[headers.index('S.O. all transcripts')]
+                            for transcript in transcripts.split(','):
+                                if transcript:
+                                    mat = SOtranscripts.search(transcript)
+                                    ref_fullseq = getSequence(mat.group(1).split('.')[0])
+                                    if ref_fullseq:
+                                        aa_changes = {mat.group(2): [aa_changes.values()[0][0]]}
+                                        break
+                        if ref_fullseq:
+                            # Sorts the amino acid changes
+                            positions = {}
+                            for aa_change in aa_changes:
+                                m = reg_seq_change.search(aa_change)
+                                aa_protpos = int(m.group(2))
+                                aa_peppos = aa_changes[aa_change][0]
+                                aa_startpos = aa_protpos - aa_peppos - 1
+                                if aa_startpos in positions:
+                                    positions[aa_startpos].append(aa_change)
+                                else:
+                                    positions[aa_startpos] = [aa_change]
+                            # Goes through the sorted categories to mutate the Ensembl peptide
+                            # (uses proBED peptide as a reference)
+                            for pep_protpos in positions:
+                                ref_seq = ref_fullseq[pep_protpos:pep_protpos+len(pepseq)]
+                                muts = positions[pep_protpos]
+                                options = []
+                                mut_seq = ref_seq
+                                for mut in muts:
+                                    m = reg_seq_change.search(mut)
+                                    ref_aa = m.group(1)
+                                    mut_pos = int(m.group(2))
+                                    alt_aa = m.group(3)
+                                    pep_mutpos = mut_pos - pep_protpos - 1
+                                    if (ref_seq[pep_mutpos] == ref_aa
+                                            and (pepseq[pep_mutpos] == alt_aa
+                                            or pepseq[pep_mutpos] == ref_aa)):
+                                        if pepseq[pep_mutpos] == ref_aa:
+                                            mut_seq = (mut_seq[:pep_mutpos] + ref_aa
+                                                       + mut_seq[pep_mutpos+1:])
+                                        else:
+                                            mut_seq = (mut_seq[:pep_mutpos] + alt_aa
+                                                       + mut_seq[pep_mutpos+1:])
+                                    else:
+                                        break
+                                # Adds the mutated peptide and reference peptide if mutated correctly
+                                if pepseq == mut_seq:
+                                    cells[n+1] = pepseq
+                                    cells[n] = ref_seq
+                tsvout.writerow(cells)
+
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravatp_submit.xml	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,296 @@
+<tool id="cravatp_submit" name="CRAVAT-P Submit, Intersect, Check, and Retrieve" version="1.0.0">
+    <description>| Submits, intersects, checks for, and retrieves data for cancer annotation.</description>
+  <command detect_errors="aggressive">
+  <![CDATA[
+#if $proteo.proteoInput == 'yes':
+    #if '$analysis.type' == 'CHASM' or '$analysis.type' == 'CHASM+VEST':
+        python '$__tool_directory__/cravatp_submit.py' '$input' '$GRCh' '$variant' '$gene' '$noncoding' '$error' '$analysis.type' --classifier '$analysis.classifier' --proBED '$proBED' --intersectOnly '$proteo.intersectedVariants' --vcfOutput '$vcf_output'
+    #else: 
+        python '$__tool_directory__/cravatp_submit.py' '$input' '$GRCh' '$variant' '$gene' '$noncoding' '$error' '$analysis.type' --proBED '$proBED' --intersectOnly '$proteo.intersectedVariants' --vcfOutput '$vcf_output' 
+    #end if
+#else:
+    #if $analysis.type == 'CHASM' or $analysis.type == 'CHASM+VEST':
+        python '$__tool_directory__/cravatp_submit.py' '$input' '$GRCh' '$variant' '$gene' '$noncoding' '$error' '$analysis.type' --classifier '$analysis.classifier' 
+    #else: 
+        python '$__tool_directory__/cravatp_submit.py' '$input' '$GRCh' '$variant' '$gene' '$noncoding' '$error' '$analysis.type'
+    #end if
+#end if
+]]></command>
+  
+  <inputs>
+    <param format="vcf" name="input" type="data" label="Source file" help="Accepts transcriptomic or genomic inputs (e.g., tabular, VCF). Additional details can be found below."></param>
+    <conditional name="proteo">
+      <param name="proteoInput" type="select" label="Intersect with proteogenomic input?" help="Source file (first input) must be in genomic input to enable intersection with this proteogenomic file.">
+        <option value="yes">Yes</option>
+        <option value="no" selected="true">No</option>
+      </param>
+      <when value="yes">
+        <param format="BED" name="proBED" type="data" label="Peptides with Genomic Coordinates (ProBED Format)"></param>
+        <param name="intersectedVariants" type="boolean" checked="false" label="Submit only intersected variants?" help="Submits the intersected portion of the genomic file to CRAVAT's server. Restricting analysis to only intersected variants takes less time but also provides less-comprehensive results."></param>
+        <param name="output_vcf" type="boolean" checked="false" label="Output intersected genomic file?" help="The intersected genomic file (e.g., VCF) will be included as a result."></param>
+      </when>
+      <when value="no">
+      </when>
+    </conditional>
+    <conditional name="analysis">
+      <param format="tabular" name="type" type="select" label="Analysis Program" help="VEST and CHASM are machine learning methods for predicting the pathogenicity and functional significance of variants, respectively.">
+          <option value="None">None</option>
+          <option value="CHASM">CHASM</option>
+          <option value="VEST">VEST</option>
+          <option value="CHASM+VEST">CHASM and VEST</option>
+      </param>
+      <when value="None"/>
+      <when value="VEST"/>
+      <when value="CHASM">
+        <param format="tabular" name="classifier" type="select" label="CHASM Classifier">
+          <option value="Bladder">Bladder</option>
+          <option value="Blood-Lymphocyte">Blood-Lymphocyte</option>
+          <option value="Blood-Myeloid">Blood-Myeloid</option>
+          <option value="Brain-Glioblastoma-Multiforme">Brain-Glioblastoma-Multiforme</option>
+          <option value="Brain-Lower-Grade-Glioma">Brain-Lower-Grade-Glioma</option>
+          <option value="Breast">Breast</option>
+          <option value="Cervix">Cervix</option>
+          <option value="Colon">Colon</option>
+          <option value="GID">GID</option>
+          <option value="Head-and-Neck">Head-and-Neck</option>
+          <option value="Kidney-Chromophobe">Kidney-Chromophobe</option>
+          <option value="Kidney-Clear-Cell">Kidney-Clear-Cell</option>
+          <option value="Kidney-Papillary-Cell">Kidney-Papillary-Cell</option>
+          <option value="Liver-Nonviral">Liver-Nonviral</option>
+          <option value="Liver-Viral">Liver-Viral</option>
+          <option value="Lung-Adenocarcinoma">Lung-Adenocarcinoma</option>
+          <option value="Lung-Squamous-Cell">Lung-Squamous-Cell</option>
+          <option value="Other">Other</option>
+          <option value="Ovary">Ovary</option>
+          <option value="Pancreas">Pancreas</option>
+          <option value="Prostate-Adenocarcinoma">Prostate-Adenocarcinoma</option>
+          <option value="Rectum">Rectum</option>
+          <option value="Skin">Skin</option>
+          <option value="Stomach">Stomach</option>
+          <option value="Thyroid">Thyroid</option>
+          <option value="Uterus">Uterus</option>
+        </param>
+      </when>
+      <when value="CHASM+VEST">
+        <param format="tabular" name="classifier" type="select" label="CHASM Classifier">
+          <option value="Bladder">Bladder</option>
+          <option value="Blood-Lymphocyte">Blood-Lymphocyte</option>
+          <option value="Blood-Myeloid">Blood-Myeloid</option>
+          <option value="Brain-Glioblastoma-Multiforme">Brain-Glioblastoma-Multiforme</option>
+          <option value="Brain-Lower-Grade-Glioma">Brain-Lower-Grade-Glioma</option>
+          <option value="Breast">Breast</option>
+          <option value="Cervix">Cervix</option>
+          <option value="Colon">Colon</option>
+          <option value="GID">GID</option>
+          <option value="Head-and-Neck">Head-and-Neck</option>
+          <option value="Kidney-Chromophobe">Kidney-Chromophobe</option>
+          <option value="Kidney-Clear-Cell">Kidney-Clear-Cell</option>
+          <option value="Kidney-Papillary-Cell">Kidney-Papillary-Cell</option>
+          <option value="Liver-Nonviral">Liver-Nonviral</option>
+          <option value="Liver-Viral">Liver-Viral</option>
+          <option value="Lung-Adenocarcinoma">Lung-Adenocarcinoma</option>
+          <option value="Lung-Squamous-Cell">Lung-Squamous-Cell</option>
+          <option value="Other">Other</option>
+          <option value="Ovary">Ovary</option>
+          <option value="Pancreas">Pancreas</option>
+          <option value="Prostate-Adenocarcinoma">Prostate-Adenocarcinoma</option>
+          <option value="Rectum">Rectum</option>
+          <option value="Skin">Skin</option>
+          <option value="Stomach">Stomach</option>
+          <option value="Thyroid">Thyroid</option>
+          <option value="Uterus">Uterus</option>
+        </param>
+      </when>
+    </conditional>
+    <!-- TODO: programatically retrieve the GRCh from a dataset rather than manually selecting it.-->
+    <param format="tabular" name="GRCh" type="select" label="Genome Reference Consortium Human Build (GRCh)" 
+        help="The default human reference genome used for annotation is GRCh38, released on December 24th, 2013 from the Genome Reference Consortium.">
+      <option value="GRCh38">GRCh38/hg38</option>
+      <option value="GRCh37">GRCh37/hg19</option>
+    </param>
+  </inputs>
+  <outputs>
+    <collection name="results" type="list" label="CRAVAT Results on ${on_string}">
+      <data format="tabular" label="CRAVAT: Gene Level Annotation Report on ${on_string}" name="gene" />
+      <data format="tabular" label="CRAVAT: Variant Report on ${on_string}" name="variant" />
+      <data format="tabular" label="CRAVAT: Non-coding Variant Report on ${on_string}" name="noncoding" />
+      <data format="tabular" label="CRAVAT: Errors on ${on_string}" name="error" />
+    </collection>
+    <data format="vcf" label="Intersected VCF on ${on_string}" name="vcf_output">
+        <filter>proteo['proteoInput'] == 'yes' and proteo['output_vcf']</filter>
+      </data>
+  </outputs>
+  <tests>
+    <!-- GRCh38/hg38 and no analysis test case -->
+    <test>
+      <param name="input" value="Freebayes_one-variant.vcf"/>
+      <param name="GRCh" value="GRCh38"/>
+      <param name="variant" value="variant.tsv"/>
+      <param name="gene" value="gene.tsv"/>
+      <param name="noncoding" value="noncoding.tsv"/>
+      <param name="error" value="error.tsv"/>
+      <param name="type" value="None"/>
+      <output_collection name="results" type="list">
+        <element name="variant">
+          <assert_contents>
+            <has_text text="#Variant Report" />
+            <has_text text="hg38"/>
+            <has_text text="UPF1" />
+            <not_has_text text="VEST" />
+          </assert_contents>
+        </element>
+      </output_collection>
+    </test>
+     <!-- GRCh38/hg38 and no analysis test case -->
+    <test>
+      <param name="input" value="Freebayes_one-variant.vcf"/>
+      <param name="GRCh" value="GRCh38"/>
+      <param name="variant" value="variant.tsv"/>
+      <param name="gene" value="gene.tsv"/>
+      <param name="noncoding" value="noncoding.tsv"/>
+      <param name="error" value="error.tsv"/>
+      <param name="type" value="None"/>
+      <output_collection name="results" type="list">
+        <element name="variant">
+          <assert_contents>
+            <has_text text="#Variant Report" />
+            <has_text text="hg38"/>
+            <has_text text="UPF1" />
+            <not_has_text text="VEST" />
+          </assert_contents>
+        </element>
+      </output_collection>
+    </test>
+    <!-- GRCh37/hg19 and no analysis test case -->
+    <test>
+      <param name="input" value="Freebayes_one-variant.vcf"/>
+      <param name="GRCh" value="GRCh37"/>
+      <param name="variant" value="variant.tsv"/>
+      <param name="gene" value="gene.tsv"/>
+      <param name="noncoding" value="noncoding.tsv"/>
+      <param name="error" value="error.tsv"/>
+      <param name="type" value="None"/>
+      <output_collection name="results" type="list">
+        <element name="variant">
+          <assert_contents>
+            <has_text text="#Variant Report" />
+            <has_text text="hg19"/>
+            <not_has_text text="VEST" />
+          </assert_contents>
+        </element>
+      </output_collection>
+    </test>
+    <!-- CHASM with "Breast" classifier test case -->
+    <test>
+      <param name="input" value="Freebayes_one-variant.vcf"/>
+      <param name="GRCh" value="GRCh38"/>
+      <param name="variant" value="variant.tsv"/>
+      <param name="gene" value="gene.tsv"/>
+      <param name="noncoding" value="noncoding.tsv"/>
+      <param name="error" value="error.tsv"/>
+      <param name="type" value="CHASM"/>
+      <param name="classifier" value="Breast"/>
+      <output_collection name="results" type="list">
+        <element name="variant">
+          <assert_contents>
+            <has_text text="hg38"/>
+            <has_text text="UPF1" />
+            <has_text text="Breast" />
+            <has_text text="#Variant Report" />
+            <not_has_text text="VEST" />
+          </assert_contents>
+        </element>
+      </output_collection>
+    </test>
+    <!-- Proteogenomic test case -->
+    <test>
+      <param name="input" value="Freebayes_one-variant.vcf"/>
+      <param name="GRCh" value="GRCh38"/>
+      <param name="variant" value="variant.tsv"/>
+      <param name="gene" value="gene.tsv"/>
+      <param name="noncoding" value="noncoding.tsv"/>
+      <param name="error" value="error.tsv"/>
+      <param name="type" value="CHASM" />
+      <param name="classifier" value="Breast" />
+      <param name="proteoInput" value="yes" />
+      <param name="proBED" value="MCF7_proBed.bed"/>
+      <output_collection name="results" type="list">
+        <element name="variant">
+          <assert_contents>
+            <has_text text="#Variant Report" />
+            <has_text text="hg38"/>
+            <has_text text="UPF1" />
+            <has_text text="EAIDSPVSFLVLHNQIR" />
+          </assert_contents>
+        </element>
+      </output_collection>
+    </test>
+    <!-- "Output intersected VCF" test case -->
+    <test>
+      <param name="input" value="Freebayes_one-variant.vcf"/>
+      <param name="GRCh" value="GRCh38"/>
+      <param name="variant" value="variant.tsv"/>
+      <param name="gene" value="gene.tsv"/>
+      <param name="noncoding" value="noncoding.tsv"/>
+      <param name="error" value="error.tsv"/>
+      <param name="type" value="CHASM" />
+      <param name="classifier" value="Breast" />
+      <param name="proteoInput" value="yes" />
+      <param name="proBED" value="MCF7_proBed.bed"/>
+      <param name="output_vcf" value="true"/>
+      <output name="vcf_output" file="results/intersected_vcf.vcf"/>
+    </test>
+    <!-- "Only intersected proteogenomic variants submitted" test case-->
+    <test>
+      <param name="input" value="Freebayes_two-variants.vcf"/>
+      <param name="GRCh" value="GRCh38"/>
+      <param name="variant" value="variant.tsv"/>
+      <param name="gene" value="gene.tsv"/>
+      <param name="noncoding" value="noncoding.tsv"/>
+      <param name="error" value="error.tsv"/>
+      <param name="type" value="CHASM" />
+      <param name="classifier" value="Breast" />
+      <param name="proteoInput" value="yes" />
+      <param name="proBED" value="MCF7_proBed.bed"/>
+      <param name="intersectedVariants" value="true" />
+      <output_collection name="results" type="list">
+        <element name="variant">
+          <assert_contents>
+            <has_text text="hg38"/>
+            <has_text text="UPF1" />
+            <not_has_text text="CRABP2"/>
+          </assert_contents>
+        </element>
+      </output_collection>
+    </test>
+  </tests>
+  <help><![CDATA[
+    This tool submits, checks for, and retrieves data for cancer annotation from the CRAVAT platform at https://www.cravat.us. 
+    For additional details on input format, visit this link: http://cravat.us/CRAVAT/help.jsp.
+
+-----
+
+**Input Type Example:**
+
+  CRAVAT Format (*Genomic-coordinate format*)
+
+    =====  =====  =========  ======  =========  =========  ====================
+    UID    Chr.   Position   Strand  Ref. base  Alt. base  Sample ID (optional)
+    =====  =====  =========  ======  =========  =========  ====================
+    TR1    chr17  7674188    \-      G          T          TCGA-02-0231
+    TR2    chr10  121520166  \-      G          A          TCGA-02-3512
+    TR3    chr13  48459831   \+      C          A          TCGA-02-3532
+    TR4    chr7   116777451  \+      G          T          TCGA-02-1523
+    TR5    chr7   140753336  \-      T          A          TCGA-02-0023
+    TR6    chr17  39724745   \+      G          T          TCGA-02-0252
+    Ins1   chr17  39724745   \+      \-         T          TCGA-02-0252
+    Del1   chr17  39724745   \+      A          \-         TCGA-02-0252
+    CSub1  chr2   39644095   \+      ATGCT      GA         TCGA-02-0252
+    =====  =====  =========  ======  =========  =========  ====================
+]]>
+  </help>
+  <citations>
+    <citation type="doi">10.1158/0008-5472.CAN-17-0338</citation>
+    <citation type="doi">10.1186/s13059-017-1377-x</citation>
+  </citations>
+</tool>
Binary file test-data/._variant.tsv has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Freebayes.vcf	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,548 @@
+##fileformat=VCFv4.2
+##fileDate=20180518
+##source=freeBayes v1.1.0-46-g8d2b3a0-dirty
+##reference=/panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa
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+##contig=<ID=chr19_KI270931v1_alt,length=170148>
+##contig=<ID=chr19_KI270932v1_alt,length=215732>
+##contig=<ID=chr19_KI270933v1_alt,length=170537>
+##contig=<ID=chr19_GL000209v2_alt,length=177381>
+##contig=<ID=chr3_KI270934v1_alt,length=163458>
+##contig=<ID=chr6_GL000253v2_alt,length=4677643>
+##contig=<ID=chr19_GL949749v2_alt,length=1091841>
+##contig=<ID=chr3_KI270935v1_alt,length=197351>
+##contig=<ID=chr6_GL000254v2_alt,length=4827813>
+##contig=<ID=chr19_GL949750v2_alt,length=1066390>
+##contig=<ID=chr3_KI270936v1_alt,length=164170>
+##contig=<ID=chr6_GL000255v2_alt,length=4606388>
+##contig=<ID=chr19_GL949751v2_alt,length=1002683>
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+##contig=<ID=chr6_GL000256v2_alt,length=4929269>
+##contig=<ID=chr19_GL949752v1_alt,length=987100>
+##contig=<ID=chr6_KI270758v1_alt,length=76752>
+##contig=<ID=chr19_GL949753v2_alt,length=796479>
+##contig=<ID=chr19_KI270938v1_alt,length=1066800>
+##contig=<ID=chrM,length=16569>
+##contig=<ID=chrUn_KI270302v1,length=2274>
+##contig=<ID=chrUn_KI270304v1,length=2165>
+##contig=<ID=chrUn_KI270303v1,length=1942>
+##contig=<ID=chrUn_KI270305v1,length=1472>
+##contig=<ID=chrUn_KI270322v1,length=21476>
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+##contig=<ID=chrUn_KI270310v1,length=1201>
+##contig=<ID=chrUn_KI270316v1,length=1444>
+##contig=<ID=chrUn_KI270315v1,length=2276>
+##contig=<ID=chrUn_KI270312v1,length=998>
+##contig=<ID=chrUn_KI270311v1,length=12399>
+##contig=<ID=chrUn_KI270317v1,length=37690>
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+##contig=<ID=chrUn_KI270468v1,length=4055>
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+##contig=<ID=chrUn_KI270516v1,length=1300>
+##contig=<ID=chrUn_KI270512v1,length=22689>
+##contig=<ID=chrUn_KI270519v1,length=138126>
+##contig=<ID=chrUn_KI270522v1,length=5674>
+##contig=<ID=chrUn_KI270511v1,length=8127>
+##contig=<ID=chrUn_KI270515v1,length=6361>
+##contig=<ID=chrUn_KI270507v1,length=5353>
+##contig=<ID=chrUn_KI270517v1,length=3253>
+##contig=<ID=chrUn_KI270529v1,length=1899>
+##contig=<ID=chrUn_KI270528v1,length=2983>
+##contig=<ID=chrUn_KI270530v1,length=2168>
+##contig=<ID=chrUn_KI270539v1,length=993>
+##contig=<ID=chrUn_KI270538v1,length=91309>
+##contig=<ID=chrUn_KI270544v1,length=1202>
+##contig=<ID=chrUn_KI270548v1,length=1599>
+##contig=<ID=chrUn_KI270583v1,length=1400>
+##contig=<ID=chrUn_KI270587v1,length=2969>
+##contig=<ID=chrUn_KI270580v1,length=1553>
+##contig=<ID=chrUn_KI270581v1,length=7046>
+##contig=<ID=chrUn_KI270579v1,length=31033>
+##contig=<ID=chrUn_KI270589v1,length=44474>
+##contig=<ID=chrUn_KI270590v1,length=4685>
+##contig=<ID=chrUn_KI270584v1,length=4513>
+##contig=<ID=chrUn_KI270582v1,length=6504>
+##contig=<ID=chrUn_KI270588v1,length=6158>
+##contig=<ID=chrUn_KI270593v1,length=3041>
+##contig=<ID=chrUn_KI270591v1,length=5796>
+##contig=<ID=chrUn_KI270330v1,length=1652>
+##contig=<ID=chrUn_KI270329v1,length=1040>
+##contig=<ID=chrUn_KI270334v1,length=1368>
+##contig=<ID=chrUn_KI270333v1,length=2699>
+##contig=<ID=chrUn_KI270335v1,length=1048>
+##contig=<ID=chrUn_KI270338v1,length=1428>
+##contig=<ID=chrUn_KI270340v1,length=1428>
+##contig=<ID=chrUn_KI270336v1,length=1026>
+##contig=<ID=chrUn_KI270337v1,length=1121>
+##contig=<ID=chrUn_KI270363v1,length=1803>
+##contig=<ID=chrUn_KI270364v1,length=2855>
+##contig=<ID=chrUn_KI270362v1,length=3530>
+##contig=<ID=chrUn_KI270366v1,length=8320>
+##contig=<ID=chrUn_KI270378v1,length=1048>
+##contig=<ID=chrUn_KI270379v1,length=1045>
+##contig=<ID=chrUn_KI270389v1,length=1298>
+##contig=<ID=chrUn_KI270390v1,length=2387>
+##contig=<ID=chrUn_KI270387v1,length=1537>
+##contig=<ID=chrUn_KI270395v1,length=1143>
+##contig=<ID=chrUn_KI270396v1,length=1880>
+##contig=<ID=chrUn_KI270388v1,length=1216>
+##contig=<ID=chrUn_KI270394v1,length=970>
+##contig=<ID=chrUn_KI270386v1,length=1788>
+##contig=<ID=chrUn_KI270391v1,length=1484>
+##contig=<ID=chrUn_KI270383v1,length=1750>
+##contig=<ID=chrUn_KI270393v1,length=1308>
+##contig=<ID=chrUn_KI270384v1,length=1658>
+##contig=<ID=chrUn_KI270392v1,length=971>
+##contig=<ID=chrUn_KI270381v1,length=1930>
+##contig=<ID=chrUn_KI270385v1,length=990>
+##contig=<ID=chrUn_KI270382v1,length=4215>
+##contig=<ID=chrUn_KI270376v1,length=1136>
+##contig=<ID=chrUn_KI270374v1,length=2656>
+##contig=<ID=chrUn_KI270372v1,length=1650>
+##contig=<ID=chrUn_KI270373v1,length=1451>
+##contig=<ID=chrUn_KI270375v1,length=2378>
+##contig=<ID=chrUn_KI270371v1,length=2805>
+##contig=<ID=chrUn_KI270448v1,length=7992>
+##contig=<ID=chrUn_KI270521v1,length=7642>
+##contig=<ID=chrUn_GL000195v1,length=182896>
+##contig=<ID=chrUn_GL000219v1,length=179198>
+##contig=<ID=chrUn_GL000220v1,length=161802>
+##contig=<ID=chrUn_GL000224v1,length=179693>
+##contig=<ID=chrUn_KI270741v1,length=157432>
+##contig=<ID=chrUn_GL000226v1,length=15008>
+##contig=<ID=chrUn_GL000213v1,length=164239>
+##contig=<ID=chrUn_KI270743v1,length=210658>
+##contig=<ID=chrUn_KI270744v1,length=168472>
+##contig=<ID=chrUn_KI270745v1,length=41891>
+##contig=<ID=chrUn_KI270746v1,length=66486>
+##contig=<ID=chrUn_KI270747v1,length=198735>
+##contig=<ID=chrUn_KI270748v1,length=93321>
+##contig=<ID=chrUn_KI270749v1,length=158759>
+##contig=<ID=chrUn_KI270750v1,length=148850>
+##contig=<ID=chrUn_KI270751v1,length=150742>
+##contig=<ID=chrUn_KI270752v1,length=27745>
+##contig=<ID=chrUn_KI270753v1,length=62944>
+##contig=<ID=chrUn_KI270754v1,length=40191>
+##contig=<ID=chrUn_KI270755v1,length=36723>
+##contig=<ID=chrUn_KI270756v1,length=79590>
+##contig=<ID=chrUn_KI270757v1,length=71251>
+##contig=<ID=chrUn_GL000214v1,length=137718>
+##contig=<ID=chrUn_KI270742v1,length=186739>
+##contig=<ID=chrUn_GL000216v2,length=176608>
+##contig=<ID=chrUn_GL000218v1,length=161147>
+##contig=<ID=chrX,length=156040895>
+##contig=<ID=chrY,length=57227415>
+##contig=<ID=chrY_KI270740v1_random,length=37240>
+##phasing=none
+##commandline="freebayes --region chrY_KI270740v1_random:0..37240 --bam b_0.bam --fasta-reference /panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa --vcf ./vcf_output/part_chrY_KI270740v1_random:0..37240.vcf"
+##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
+##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
+##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
+##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
+##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
+##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
+##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
+##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
+##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
+##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
+##INFO=<ID=QR,Number=1,Type=Integer,Description="Reference allele quality sum in phred">
+##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
+##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
+##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
+##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
+##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
+##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
+##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
+##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
+##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
+##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
+##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
+##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
+##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
+##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
+##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
+##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
+##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
+##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
+##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
+##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
+##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
+##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
+##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
+##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
+##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
+##FORMAT=<ID=GQ,Number=1,Type=Float,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
+##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
+##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
+##FORMAT=<ID=QR,Number=1,Type=Integer,Description="Sum of quality of the reference observations">
+##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
+##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
+##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	unknown
+chr1	156701052	.	C	T	122.853	.	AB=0.4;ABP=4.74748;AC=1;AF=0.5;AN=2;AO=8;CIGAR=1X;DP=20;DPB=20;DPRA=0;EPP=4.09604;EPPR=4.45795;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=11.0181;PAIRED=1;PAIREDR=0.833333;PAO=0;PQA=0;PQR=0;PRO=0;QA=255;QR=217;RO=6;RPL=0;RPP=20.3821;RPPR=4.45795;RPR=8;RUN=1;SAF=5;SAP=4.09604;SAR=3;SRF=6;SRP=16.0391;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:20:6,8:6:217:8:255:-18.7505,0,-15.3493
+chr1	156701053	.	CT	AG	24.1256	.	AB=0.666667;ABP=3.73412;AC=1;AF=0.5;AN=2;AO=2;CIGAR=2X;DP=3;DPB=4;DPRA=0;EPP=7.35324;EPPR=5.18177;GTI=0;LEN=2;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=2.97054;PAIRED=0.5;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=2;QA=72;QR=38;RO=1;RPL=0;RPP=7.35324;RPPR=5.18177;RPR=2;RUN=1;SAF=2;SAP=7.35324;SAR=0;SRF=1;SRP=5.18177;SRR=0;TYPE=complex	GT:DP:AD:RO:QR:AO:QA:GL	0/1:3:1,2:1:38:2:72:-5.33122,0,-2.03897
+chr1	156705422	.	T	C	126013	.	AB=0.318664;ABP=5149.54;AC=1;AF=0.5;AN=2;AO=5742;CIGAR=1X;DP=18019;DPB=18019;DPRA=0;EPP=282.707;EPPR=1125.45;GTI=0;LEN=1;MEANALT=3;MQM=59.9692;MQMR=59.9856;NS=1;NUMALT=1;ODDS=29015.6;PAIRED=0.984674;PAIREDR=0.981657;PAO=0;PQA=0;PQR=0;PRO=0;QA=208149;QR=444948;RO=12266;RPL=3615;RPP=840.341;RPPR=1076.08;RPR=2127;RUN=1;SAF=3392;SAP=413.618;SAR=2350;SRF=6908;SRP=428.329;SRR=5358;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:18019:12266,5742:12266:444948:5742:208149:-13290.6,0,-34589.6
+chr11	27889736	.	C	T	52.1986	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=2;CIGAR=1X;DP=2;DPB=2;DPRA=0;EPP=7.35324;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=7.37776;PAIRED=0;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=74;QR=0;RO=0;RPL=0;RPP=7.35324;RPPR=0;RPR=2;RUN=1;SAF=2;SAP=7.35324;SAR=0;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:2:0,2:0:0:2:74:-7.02577,-0.60206,0
+chr11	27889762	.	T	A	35.1213	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=2;CIGAR=1X;DP=2;DPB=2;DPRA=0;EPP=7.35324;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=7.37776;PAIRED=0;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=56;QR=0;RO=0;RPL=2;RPP=7.35324;RPPR=0;RPR=0;RUN=1;SAF=2;SAP=7.35324;SAR=0;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:2:0,2:0:0:2:56:-5.31791,-0.60206,0
+chr11	27889795	.	T	C	295.783	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=16;CIGAR=1X;DP=18;DPB=18;DPRA=0;EPP=29.6108;EPPR=7.35324;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=22.1246;PAIRED=0;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=471;QR=30;RO=2;RPL=0;RPP=37.7539;RPPR=7.35324;RPR=16;RUN=1;SAF=1;SAP=29.6108;SAR=15;SRF=2;SRP=7.35324;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:18:2,16:2:30:16:471:-39.8133,-2.56857,0
+chr11	27889819	.	A	G	765.194	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=32;CIGAR=1X;DP=33;DPB=33;DPRA=0;EPP=9.79615;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=48.9666;PAIRED=0.03125;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=990;QR=0;RO=0;RPL=0;RPP=72.4974;RPPR=0;RPR=32;RUN=1;SAF=11;SAP=9.79615;SAR=21;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:33:0,32:0:0:32:990:-89.197,-9.63296,0
+chr11	27889843	.	A	T	948.794	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=35;CIGAR=1X;DP=36;DPB=36;DPRA=0;EPP=8.03571;EPPR=5.18177;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=49.5538;PAIRED=0.0571429;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1109;QR=15;RO=1;RPL=12;RPP=10.5174;RPPR=5.18177;RPR=23;RUN=1;SAF=12;SAP=10.5174;SAR=23;SRF=0;SRP=5.18177;SRR=1;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:36:1,35:1:15:35:1109:-98.5725,-9.33709,0
+chr11	27889860	.	C	T	170.937	.	AB=0.325;ABP=13.6505;AC=1;AF=0.5;AN=2;AO=13;CIGAR=1X;DP=40;DPB=40;DPRA=0;EPP=3.17734;EPPR=9.52472;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=39.3596;PAIRED=0.153846;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=390;QR=888;RO=27;RPL=8;RPP=4.51363;RPPR=12.7417;RPR=5;RUN=1;SAF=8;SAP=4.51363;SAR=5;SRF=5;SRP=26.2531;SRR=22;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:40:27,13:27:888:13:390:-23.341,0,-68.1636
+chr11	27889934	.	T	A	75.8995	.	AB=0.5;ABP=3.0103;AC=1;AF=0.5;AN=2;AO=3;CIGAR=1X;DP=6;DPB=6;DPRA=0;EPP=3.73412;EPPR=7.35324;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=6.74621;PAIRED=0.333333;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=114;QR=32;RO=2;RPL=3;RPP=9.52472;RPPR=7.35324;RPR=0;RUN=1;SAF=1;SAP=3.73412;SAR=2;SRF=0;SRP=7.35324;SRR=2;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:6:2,3:2:32:3:114:-8.91977,0,-1.38149
+chr12	6560786	.	A	C,T	0.671284	.	AB=0.333333,0.388889;ABP=7.35324,4.9405;AC=1,0;AF=0.5,0;AN=2;AO=6,7;CIGAR=1X,1X;DP=18;DPB=18;DPRA=0,0;EPP=16.0391,3.32051;EPPR=3.0103;GTI=0;LEN=1,1;MEANALT=3,3;MQM=60,51.5714;MQMR=60;NS=1;NUMALT=2;ODDS=2.30652;PAIRED=1,1;PAIREDR=1;PAO=0,0;PQA=0,0;PQR=0;PRO=0;QA=90,100;QR=76;RO=2;RPL=0,0;RPP=16.0391,18.2106;RPPR=3.0103;RPR=6,7;RUN=1,1;SAF=0,3;SAP=16.0391,3.32051;SAR=6,4;SRF=2;SRP=7.35324;SRR=0;TYPE=snp,snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:18:2,6,7:2:76:6,7:90,100:-5.69842,0,-4.46814,-0.502973,-0.533287,-4.67076
+chr12	6561055	.	T	C	14340.8	.	AB=0.235264;ABP=2357.67;AC=1;AF=0.5;AN=2;AO=910;CIGAR=1X;DP=3868;DPB=3868;DPRA=0;EPP=7.21962;EPPR=59.3944;GTI=0;LEN=1;MEANALT=2;MQM=59.9352;MQMR=59.7205;NS=1;NUMALT=1;ODDS=3302.08;PAIRED=0.983516;PAIREDR=0.990186;PAO=0;PQA=0;PQR=0;PRO=0;QA=33224;QR=106496;RO=2955;RPL=107;RPP=1158.94;RPPR=4030.18;RPR=803;RUN=1;SAF=481;SAP=9.46268;SAR=429;SRF=1663;SRP=104.155;SRR=1292;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:3868:2955,910:2955:106496:910:33224:-1821.72,0,-8372.79
+chr12	110033192	.	T	C	53.1444	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=2;CIGAR=1X;DP=2;DPB=2;DPRA=0;EPP=7.35324;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=7.37776;PAIRED=0;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=75;QR=0;RO=0;RPL=0;RPP=7.35324;RPPR=0;RPR=2;RUN=1;SAF=0;SAP=7.35324;SAR=2;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:2:0,2:0:0:2:75:-7.12034,-0.60206,0
+chr12	110339630	.	C	T	48828.1	.	AB=0.268901;ABP=4224.36;AC=1;AF=0.5;AN=2;AO=2447;CIGAR=1X;DP=9100;DPB=9100;DPRA=0;EPP=710.668;EPPR=1883.3;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=11243.1;PAIRED=0.985288;PAIREDR=0.980156;PAO=0;PQA=0;PQR=0;PRO=0;QA=90595;QR=244569;RO=6652;RPL=1094;RPP=62.5381;RPPR=155.737;RPR=1353;RUN=1;SAF=1227;SAP=3.05378;SAR=1220;SRF=3354;SRP=4.03401;SRR=3298;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:9100:6652,2447:6652:244569:2447:90595:-5409.03,0,-19257.6
+chr14	94079142	.	T	C	0	.	AB=0;ABP=0;AC=0;AF=0;AN=2;AO=756;CIGAR=1X;DP=3707;DPB=3707;DPRA=0;EPP=71.1302;EPPR=383.929;GTI=0;LEN=1;MEANALT=3;MQM=23.164;MQMR=22.8823;NS=1;NUMALT=1;ODDS=1140.53;PAIRED=0.994709;PAIREDR=0.99491;PAO=0;PQA=0;PQR=0;PRO=0;QA=27331;QR=106693;RO=2947;RPL=419;RPP=22.3238;RPPR=516.755;RPR=337;RUN=1;SAF=312;SAP=53.0576;SAR=444;SRF=1285;SRP=107.737;SRR=1662;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/0:3707:2947,756:2947:106693:756:27331:0,-172.332,-2685.28
+chr14	102011985	.	A	T	12962.3	.	AB=0.301267;ABP=734.044;AC=1;AF=0.5;AN=2;AO=642;CIGAR=1X;DP=2131;DPB=2131;DPRA=0;EPP=6.47383;EPPR=23.6897;GTI=0;LEN=1;MEANALT=3;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=2984.69;PAIRED=0.995327;PAIREDR=0.98117;PAO=0;PQA=0;PQR=0;PRO=0;QA=22490;QR=51005;RO=1487;RPL=362;RPP=25.7533;RPPR=15.6405;RPR=280;RUN=1;SAF=307;SAP=5.66207;SAR=335;SRF=729;SRP=4.23842;SRR=758;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:2131:1487,642:1487:51005:642:22490:-1382.22,0,-3947.19
+chr14	102083954	.	C	T	240741	.	AB=0.203722;ABP=65019.6;AC=1;AF=0.5;AN=2;AO=17372;CIGAR=1X;DP=85273;DPB=85273;DPRA=0;EPP=2106.28;EPPR=12892.8;GTI=0;LEN=1;MEANALT=3;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=55432.6;PAIRED=0.982155;PAIREDR=0.980402;PAO=0;PQA=0;PQR=0;PRO=0;QA=637523;QR=2489236;RO=67865;RPL=5766;RPP=4266.16;RPPR=13677.6;RPR=11606;RUN=1;SAF=9063;SAP=74.0739;SAR=8309;SRF=35817;SRP=457.538;SRR=32048;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:85273:67865,17372:67865:2489236:17372:637523:-31680.6,0,-198225
+chr14	102084466	.	G	A	866755	.	AB=0.793643;ABP=29738.6;AC=1;AF=0.5;AN=2;AO=31510;CIGAR=1X;DP=39703;DPB=39703;DPRA=0;EPP=3701.63;EPPR=962.263;GTI=0;LEN=1;MEANALT=3;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=26239.5;PAIRED=0.994319;PAIREDR=0.994371;PAO=0;PQA=0;PQR=0;PRO=0;QA=1162876;QR=302820;RO=8172;RPL=24066;RPP=19043.3;RPPR=4663.58;RPR=7444;RUN=1;SAF=11974;SAP=3943.76;SAR=19536;SRF=3044;SRP=1157.05;SRR=5128;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:39703:8172,31510:8172:302820:31510:1162876:-92643.6,0,-15290.2
+chr17	82082413	.	A	C	0.015243	.	AB=0.444444;ABP=3.25157;AC=1;AF=0.5;AN=2;AO=4;CIGAR=1X;DP=9;DPB=9;DPRA=0;EPP=5.18177;EPPR=3.44459;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=5.65043;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=57;QR=158;RO=5;RPL=0;RPP=11.6962;RPPR=6.91895;RPR=4;RUN=1;SAF=1;SAP=5.18177;SAR=3;SRF=4;SRP=6.91895;SRR=1;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:9:5,4:5:158:4:57:-2.56319,0,-11.821
+chr17	82082414	.	C	G	0.0150561	.	AB=0.4;ABP=3.44459;AC=1;AF=0.5;AN=2;AO=2;CIGAR=1X;DP=5;DPB=5;DPRA=0;EPP=7.35324;EPPR=9.52472;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=5.66308;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=29;QR=110;RO=3;RPL=1;RPP=3.0103;RPPR=9.52472;RPR=1;RUN=1;SAF=1;SAP=3.0103;SAR=1;SRF=3;SRP=9.52472;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:5:3,2:3:110:2:29:-1.24983,0,-8.7554
+chr17	82082606	.	C	T	10374.8	.	AB=0.202823;ABP=2937.89;AC=1;AF=0.5;AN=2;AO=776;CIGAR=1X;DP=3826;DPB=3826;DPRA=0;EPP=22.755;EPPR=126.853;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=59.9806;NS=1;NUMALT=1;ODDS=2388.89;PAIRED=0.981959;PAIREDR=0.985569;PAO=0;PQA=0;PQR=0;PRO=0;QA=27982;QR=110520;RO=3049;RPL=338;RPP=30.9932;RPPR=253.452;RPR=438;RUN=1;SAF=422;SAP=15.9496;SAR=354;SRF=1759;SRP=159.665;SRR=1290;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:3826:3049,776:3049:110520:776:27982:-1365.58,0,-8788
+chr17	82082731	.	T	C	701.469	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=26;CIGAR=1X;DP=26;DPB=26;DPRA=0;EPP=15.0369;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=40.6488;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=888;QR=0;RO=0;RPL=22;RPP=30.0702;RPPR=0;RPR=4;RUN=1;SAF=3;SAP=36.4176;SAR=23;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:26:0,26:0:0:26:888:-80.2195,-7.82678,0
+chr17	82082763	.	G	A	91.2949	.	AB=0.6;ABP=3.87889;AC=1;AF=0.5;AN=2;AO=6;CIGAR=1X;DP=10;DPB=10;DPRA=0;EPP=16.0391;EPPR=5.18177;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=11.9868;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=221;QR=144;RO=4;RPL=6;RPP=16.0391;RPPR=5.18177;RPR=0;RUN=1;SAF=0;SAP=16.0391;SAR=6;SRF=0;SRP=11.6962;SRR=4;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:10:4,6:4:144:6:221:-17.2361,0,-10.3021
+chr19	17205335	.	A	T	0.00158993	.	AB=0.285714;ABP=5.80219;AC=1;AF=0.5;AN=2;AO=2;CIGAR=1X;DP=7;DPB=7;DPRA=0;EPP=3.0103;EPPR=6.91895;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=48.2;NS=1;NUMALT=1;ODDS=7.91247;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=28;QR=169;RO=5;RPL=0;RPP=7.35324;RPPR=13.8677;RPR=2;RUN=1;SAF=1;SAP=3.0103;SAR=1;SRF=1;SRP=6.91895;SRR=4;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:7:5,2:5:169:2:28:-0.55277,0,-10.4001
+chr19	17205444	.	T	C	206.198	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=7;CIGAR=1X;DP=7;DPB=7;DPRA=0;EPP=5.80219;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=14.3092;PAIRED=0.857143;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=249;QR=0;RO=0;RPL=2;RPP=5.80219;RPPR=0;RPR=5;RUN=1;SAF=4;SAP=3.32051;SAR=3;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:7:0,7:0:0:7:249:-22.753,-2.10721,0
+chr19	17205973	.	T	C	12243.8	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=406;CIGAR=1X;DP=406;DPB=406;DPRA=0;EPP=14.3276;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=58.4015;MQMR=0;NS=1;NUMALT=1;ODDS=567.441;PAIRED=0.985222;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=14833;QR=0;RO=0;RPL=368;RPP=585.457;RPPR=0;RPR=38;RUN=1;SAF=182;SAP=12.445;SAR=224;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:406:0,406:0:0:406:14833:-1297.85,-122.218,0
+chr19	18856059	.	C	T	10269.5	.	AB=0.248844;ABP=1306.46;AC=1;AF=0.5;AN=2;AO=592;CIGAR=1X;DP=2379;DPB=2379;DPRA=0;EPP=30.139;EPPR=172.262;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=59.9339;NS=1;NUMALT=1;ODDS=2364.65;PAIRED=0.991554;PAIREDR=0.983754;PAO=0;PQA=0;PQR=0;PRO=0;QA=21546;QR=64865;RO=1785;RPL=120;RPP=457.494;RPPR=1043.89;RPR=472;RUN=1;SAF=303;SAP=3.72923;SAR=289;SRF=873;SRP=4.86061;SRR=912;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:2379:1785,592:1785:64865:592:21546:-1222.54,0,-5112.92
+chr19	18867128	.	G	C	398.913	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=14;CIGAR=1X;DP=14;DPB=14;DPRA=0;EPP=33.4109;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=24.0133;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=523;QR=0;RO=0;RPL=11;RPP=12.937;RPPR=0;RPR=3;RUN=1;SAF=11;SAP=12.937;SAR=3;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:14:0,14:0:0:14:523:-47.4124,-4.21442,0
+chr2	231456129	.	GGATGGCT	TGATTCAC	54.047	.	AB=0.363636;ABP=4.78696;AC=1;AF=0.5;AN=2;AO=4;CIGAR=1X3M4X;DP=11;DPB=12.375;DPRA=0;EPP=3.0103;EPPR=5.80219;GTI=0;LEN=8;MEANALT=1;MQM=60;MQMR=51.5714;NS=1;NUMALT=1;ODDS=12.4448;PAIRED=1;PAIREDR=0.714286;PAO=0;PQA=0;PQR=134;PRO=4;QA=150;QR=252;RO=7;RPL=0;RPP=11.6962;RPPR=18.2106;RPR=4;RUN=1;SAF=2;SAP=3.0103;SAR=2;SRF=5;SRP=5.80219;SRR=2;TYPE=complex	GT:DP:AD:RO:QR:AO:QA:GL	0/1:11:7,4:7:252:4:150:-9.35048,0,-24.4716
+chr2	231456762	.	T	C	60.9983	.	AB=0.333333;ABP=7.35324;AC=1;AF=0.5;AN=2;AO=6;CIGAR=1X;DP=18;DPB=18;DPRA=0;EPP=3.0103;EPPR=9.52472;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=14.0454;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=181;QR=429;RO=12;RPL=0;RPP=16.0391;RPPR=29.068;RPR=6;RUN=1;SAF=3;SAP=3.0103;SAR=3;SRF=9;SRP=9.52472;SRR=3;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:18:12,6:12:429:6:181:-11.1631,0,-33.5255
+chr2	231456763	.	A	G	0.000241075	.	AB=0.25;ABP=9.52472;AC=1;AF=0.5;AN=2;AO=3;CIGAR=1X;DP=12;DPB=12;DPRA=0;EPP=9.52472;EPPR=18.2106;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=9.79893;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=39;QR=257;RO=7;RPL=0;RPP=9.52472;RPPR=18.2106;RPR=3;RUN=1;SAF=0;SAP=9.52472;SAR=3;SRF=7;SRP=18.2106;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:12:7,3:7:257:3:39:-0.481678,0,-20.2656
+chr2	231456764	.	C	T	67.7463	.	AB=0.714286;ABP=5.80219;AC=1;AF=0.5;AN=2;AO=5;CIGAR=1X;DP=7;DPB=7;DPRA=0;EPP=13.8677;EPPR=7.35324;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=3.26857;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=166;QR=76;RO=2;RPL=0;RPP=13.8677;RPPR=7.35324;RPR=5;RUN=1;SAF=5;SAP=13.8677;SAR=0;SRF=2;SRP=7.35324;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:7:2,5:2:76:5:166:-13.1558,0,-5.1076
+chr2	231457190	.	T	C	744.752	.	AB=0.221739;ABP=157.695;AC=1;AF=0.5;AN=2;AO=51;CIGAR=1X;DP=230;DPB=230;DPRA=0;EPP=3.3935;EPPR=7.38964;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=171.486;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=1858;QR=6693;RO=179;RPL=34;RPP=15.3153;RPPR=25.4408;RPR=17;RUN=1;SAF=18;SAP=12.5903;SAR=33;SRF=84;SRP=4.47817;SRR=95;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:230:179,51:179:6693:51:1858:-98.2392,0,-533.104
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Freebayes_one-variant.vcf	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,516 @@
+##fileformat=VCFv4.2
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+##contig=<ID=chrY,length=57227415>
+##contig=<ID=chrY_KI270740v1_random,length=37240>
+##phasing=none
+##commandline="freebayes --region chrY_KI270740v1_random:0..37240 --bam b_0.bam --fasta-reference /panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa --vcf ./vcf_output/part_chrY_KI270740v1_random:0..37240.vcf"
+##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
+##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
+##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
+##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
+##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
+##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
+##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
+##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
+##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
+##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
+##INFO=<ID=QR,Number=1,Type=Integer,Description="Reference allele quality sum in phred">
+##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
+##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
+##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
+##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
+##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
+##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
+##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
+##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
+##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
+##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
+##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
+##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
+##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
+##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
+##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
+##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
+##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
+##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
+##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
+##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
+##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
+##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
+##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
+##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
+##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
+##FORMAT=<ID=GQ,Number=1,Type=Float,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
+##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
+##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
+##FORMAT=<ID=QR,Number=1,Type=Integer,Description="Sum of quality of the reference observations">
+##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
+##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
+##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	unknown
+chr19	18856059	.	C	T	10269.5	.	AB=0.248844;ABP=1306.46;AC=1;AF=0.5;AN=2;AO=592;CIGAR=1X;DP=2379;DPB=2379;DPRA=0;EPP=30.139;EPPR=172.262;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=59.9339;NS=1;NUMALT=1;ODDS=2364.65;PAIRED=0.991554;PAIREDR=0.983754;PAO=0;PQA=0;PQR=0;PRO=0;QA=21546;QR=64865;RO=1785;RPL=120;RPP=457.494;RPPR=1043.89;RPR=472;RUN=1;SAF=303;SAP=3.72923;SAR=289;SRF=873;SRP=4.86061;SRR=912;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:2379:1785,592:1785:64865:592:21546:-1222.54,0,-5112.92
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Freebayes_special-cases.vcf	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,523 @@
+##fileformat=VCFv4.2
+##fileDate=20180518
+##source=freeBayes v1.1.0-46-g8d2b3a0-dirty
+##reference=/panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa
+##contig=<ID=chr1,length=248956422>
+##contig=<ID=chr10,length=133797422>
+##contig=<ID=chr11,length=135086622>
+##contig=<ID=chr11_KI270721v1_random,length=100316>
+##contig=<ID=chr12,length=133275309>
+##contig=<ID=chr13,length=114364328>
+##contig=<ID=chr14,length=107043718>
+##contig=<ID=chr14_GL000009v2_random,length=201709>
+##contig=<ID=chr14_GL000225v1_random,length=211173>
+##contig=<ID=chr14_KI270722v1_random,length=194050>
+##contig=<ID=chr14_GL000194v1_random,length=191469>
+##contig=<ID=chr14_KI270723v1_random,length=38115>
+##contig=<ID=chr14_KI270724v1_random,length=39555>
+##contig=<ID=chr14_KI270725v1_random,length=172810>
+##contig=<ID=chr14_KI270726v1_random,length=43739>
+##contig=<ID=chr15,length=101991189>
+##contig=<ID=chr15_KI270727v1_random,length=448248>
+##contig=<ID=chr16,length=90338345>
+##contig=<ID=chr16_KI270728v1_random,length=1872759>
+##contig=<ID=chr17,length=83257441>
+##contig=<ID=chr17_GL000205v2_random,length=185591>
+##contig=<ID=chr17_KI270729v1_random,length=280839>
+##contig=<ID=chr17_KI270730v1_random,length=112551>
+##contig=<ID=chr18,length=80373285>
+##contig=<ID=chr19,length=58617616>
+##contig=<ID=chr1_KI270706v1_random,length=175055>
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+##contig=<ID=chrUn_KI270320v1,length=4416>
+##contig=<ID=chrUn_KI270310v1,length=1201>
+##contig=<ID=chrUn_KI270316v1,length=1444>
+##contig=<ID=chrUn_KI270315v1,length=2276>
+##contig=<ID=chrUn_KI270312v1,length=998>
+##contig=<ID=chrUn_KI270311v1,length=12399>
+##contig=<ID=chrUn_KI270317v1,length=37690>
+##contig=<ID=chrUn_KI270412v1,length=1179>
+##contig=<ID=chrUn_KI270411v1,length=2646>
+##contig=<ID=chrUn_KI270414v1,length=2489>
+##contig=<ID=chrUn_KI270419v1,length=1029>
+##contig=<ID=chrUn_KI270418v1,length=2145>
+##contig=<ID=chrUn_KI270420v1,length=2321>
+##contig=<ID=chrUn_KI270424v1,length=2140>
+##contig=<ID=chrUn_KI270417v1,length=2043>
+##contig=<ID=chrUn_KI270422v1,length=1445>
+##contig=<ID=chrUn_KI270423v1,length=981>
+##contig=<ID=chrUn_KI270425v1,length=1884>
+##contig=<ID=chrUn_KI270429v1,length=1361>
+##contig=<ID=chrUn_KI270442v1,length=392061>
+##contig=<ID=chrUn_KI270466v1,length=1233>
+##contig=<ID=chrUn_KI270465v1,length=1774>
+##contig=<ID=chrUn_KI270467v1,length=3920>
+##contig=<ID=chrUn_KI270435v1,length=92983>
+##contig=<ID=chrUn_KI270438v1,length=112505>
+##contig=<ID=chrUn_KI270468v1,length=4055>
+##contig=<ID=chrUn_KI270510v1,length=2415>
+##contig=<ID=chrUn_KI270509v1,length=2318>
+##contig=<ID=chrUn_KI270518v1,length=2186>
+##contig=<ID=chrUn_KI270508v1,length=1951>
+##contig=<ID=chrUn_KI270516v1,length=1300>
+##contig=<ID=chrUn_KI270512v1,length=22689>
+##contig=<ID=chrUn_KI270519v1,length=138126>
+##contig=<ID=chrUn_KI270522v1,length=5674>
+##contig=<ID=chrUn_KI270511v1,length=8127>
+##contig=<ID=chrUn_KI270515v1,length=6361>
+##contig=<ID=chrUn_KI270507v1,length=5353>
+##contig=<ID=chrUn_KI270517v1,length=3253>
+##contig=<ID=chrUn_KI270529v1,length=1899>
+##contig=<ID=chrUn_KI270528v1,length=2983>
+##contig=<ID=chrUn_KI270530v1,length=2168>
+##contig=<ID=chrUn_KI270539v1,length=993>
+##contig=<ID=chrUn_KI270538v1,length=91309>
+##contig=<ID=chrUn_KI270544v1,length=1202>
+##contig=<ID=chrUn_KI270548v1,length=1599>
+##contig=<ID=chrUn_KI270583v1,length=1400>
+##contig=<ID=chrUn_KI270587v1,length=2969>
+##contig=<ID=chrUn_KI270580v1,length=1553>
+##contig=<ID=chrUn_KI270581v1,length=7046>
+##contig=<ID=chrUn_KI270579v1,length=31033>
+##contig=<ID=chrUn_KI270589v1,length=44474>
+##contig=<ID=chrUn_KI270590v1,length=4685>
+##contig=<ID=chrUn_KI270584v1,length=4513>
+##contig=<ID=chrUn_KI270582v1,length=6504>
+##contig=<ID=chrUn_KI270588v1,length=6158>
+##contig=<ID=chrUn_KI270593v1,length=3041>
+##contig=<ID=chrUn_KI270591v1,length=5796>
+##contig=<ID=chrUn_KI270330v1,length=1652>
+##contig=<ID=chrUn_KI270329v1,length=1040>
+##contig=<ID=chrUn_KI270334v1,length=1368>
+##contig=<ID=chrUn_KI270333v1,length=2699>
+##contig=<ID=chrUn_KI270335v1,length=1048>
+##contig=<ID=chrUn_KI270338v1,length=1428>
+##contig=<ID=chrUn_KI270340v1,length=1428>
+##contig=<ID=chrUn_KI270336v1,length=1026>
+##contig=<ID=chrUn_KI270337v1,length=1121>
+##contig=<ID=chrUn_KI270363v1,length=1803>
+##contig=<ID=chrUn_KI270364v1,length=2855>
+##contig=<ID=chrUn_KI270362v1,length=3530>
+##contig=<ID=chrUn_KI270366v1,length=8320>
+##contig=<ID=chrUn_KI270378v1,length=1048>
+##contig=<ID=chrUn_KI270379v1,length=1045>
+##contig=<ID=chrUn_KI270389v1,length=1298>
+##contig=<ID=chrUn_KI270390v1,length=2387>
+##contig=<ID=chrUn_KI270387v1,length=1537>
+##contig=<ID=chrUn_KI270395v1,length=1143>
+##contig=<ID=chrUn_KI270396v1,length=1880>
+##contig=<ID=chrUn_KI270388v1,length=1216>
+##contig=<ID=chrUn_KI270394v1,length=970>
+##contig=<ID=chrUn_KI270386v1,length=1788>
+##contig=<ID=chrUn_KI270391v1,length=1484>
+##contig=<ID=chrUn_KI270383v1,length=1750>
+##contig=<ID=chrUn_KI270393v1,length=1308>
+##contig=<ID=chrUn_KI270384v1,length=1658>
+##contig=<ID=chrUn_KI270392v1,length=971>
+##contig=<ID=chrUn_KI270381v1,length=1930>
+##contig=<ID=chrUn_KI270385v1,length=990>
+##contig=<ID=chrUn_KI270382v1,length=4215>
+##contig=<ID=chrUn_KI270376v1,length=1136>
+##contig=<ID=chrUn_KI270374v1,length=2656>
+##contig=<ID=chrUn_KI270372v1,length=1650>
+##contig=<ID=chrUn_KI270373v1,length=1451>
+##contig=<ID=chrUn_KI270375v1,length=2378>
+##contig=<ID=chrUn_KI270371v1,length=2805>
+##contig=<ID=chrUn_KI270448v1,length=7992>
+##contig=<ID=chrUn_KI270521v1,length=7642>
+##contig=<ID=chrUn_GL000195v1,length=182896>
+##contig=<ID=chrUn_GL000219v1,length=179198>
+##contig=<ID=chrUn_GL000220v1,length=161802>
+##contig=<ID=chrUn_GL000224v1,length=179693>
+##contig=<ID=chrUn_KI270741v1,length=157432>
+##contig=<ID=chrUn_GL000226v1,length=15008>
+##contig=<ID=chrUn_GL000213v1,length=164239>
+##contig=<ID=chrUn_KI270743v1,length=210658>
+##contig=<ID=chrUn_KI270744v1,length=168472>
+##contig=<ID=chrUn_KI270745v1,length=41891>
+##contig=<ID=chrUn_KI270746v1,length=66486>
+##contig=<ID=chrUn_KI270747v1,length=198735>
+##contig=<ID=chrUn_KI270748v1,length=93321>
+##contig=<ID=chrUn_KI270749v1,length=158759>
+##contig=<ID=chrUn_KI270750v1,length=148850>
+##contig=<ID=chrUn_KI270751v1,length=150742>
+##contig=<ID=chrUn_KI270752v1,length=27745>
+##contig=<ID=chrUn_KI270753v1,length=62944>
+##contig=<ID=chrUn_KI270754v1,length=40191>
+##contig=<ID=chrUn_KI270755v1,length=36723>
+##contig=<ID=chrUn_KI270756v1,length=79590>
+##contig=<ID=chrUn_KI270757v1,length=71251>
+##contig=<ID=chrUn_GL000214v1,length=137718>
+##contig=<ID=chrUn_KI270742v1,length=186739>
+##contig=<ID=chrUn_GL000216v2,length=176608>
+##contig=<ID=chrUn_GL000218v1,length=161147>
+##contig=<ID=chrX,length=156040895>
+##contig=<ID=chrY,length=57227415>
+##contig=<ID=chrY_KI270740v1_random,length=37240>
+##phasing=none
+##commandline="freebayes --region chrY_KI270740v1_random:0..37240 --bam b_0.bam --fasta-reference /panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa --vcf ./vcf_output/part_chrY_KI270740v1_random:0..37240.vcf"
+##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
+##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
+##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
+##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
+##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
+##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
+##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
+##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
+##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
+##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
+##INFO=<ID=QR,Number=1,Type=Integer,Description="Reference allele quality sum in phred">
+##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
+##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
+##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
+##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
+##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
+##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
+##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
+##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
+##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
+##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
+##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
+##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
+##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
+##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
+##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
+##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
+##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
+##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
+##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
+##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
+##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
+##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
+##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
+##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
+##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
+##FORMAT=<ID=GQ,Number=1,Type=Float,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
+##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
+##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
+##FORMAT=<ID=QR,Number=1,Type=Integer,Description="Sum of quality of the reference observations">
+##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
+##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
+##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	unknown
+chr1	156701053	.	CT	AG	24.1256	.	AB=0.666667;ABP=3.73412;AC=1;AF=0.5;AN=2;AO=2;CIGAR=2X;DP=3;DPB=4;DPRA=0;EPP=7.35324;EPPR=5.18177;GTI=0;LEN=2;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=2.97054;PAIRED=0.5;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=2;QA=72;QR=38;RO=1;RPL=0;RPP=7.35324;RPPR=5.18177;RPR=2;RUN=1;SAF=2;SAP=7.35324;SAR=0;SRF=1;SRP=5.18177;SRR=0;TYPE=complex	GT:DP:AD:RO:QR:AO:QA:GL	0/1:3:1,2:1:38:2:72:-5.33122,0,-2.03897
+chr12	6561055	.	T	C	14340.8	.	AB=0.235264;ABP=2357.67;AC=1;AF=0.5;AN=2;AO=910;CIGAR=1X;DP=3868;DPB=3868;DPRA=0;EPP=7.21962;EPPR=59.3944;GTI=0;LEN=1;MEANALT=2;MQM=59.9352;MQMR=59.7205;NS=1;NUMALT=1;ODDS=3302.08;PAIRED=0.983516;PAIREDR=0.990186;PAO=0;PQA=0;PQR=0;PRO=0;QA=33224;QR=106496;RO=2955;RPL=107;RPP=1158.94;RPPR=4030.18;RPR=803;RUN=1;SAF=481;SAP=9.46268;SAR=429;SRF=1663;SRP=104.155;SRR=1292;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:3868:2955,910:2955:106496:910:33224:-1821.72,0,-8372.79
+chr14	102083954	.	C	T	240741	.	AB=0.203722;ABP=65019.6;AC=1;AF=0.5;AN=2;AO=17372;CIGAR=1X;DP=85273;DPB=85273;DPRA=0;EPP=2106.28;EPPR=12892.8;GTI=0;LEN=1;MEANALT=3;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=55432.6;PAIRED=0.982155;PAIREDR=0.980402;PAO=0;PQA=0;PQR=0;PRO=0;QA=637523;QR=2489236;RO=67865;RPL=5766;RPP=4266.16;RPPR=13677.6;RPR=11606;RUN=1;SAF=9063;SAP=74.0739;SAR=8309;SRF=35817;SRP=457.538;SRR=32048;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:85273:67865,17372:67865:2489236:17372:637523:-31680.6,0,-198225
+chr19	17205335	.	A	T	0.00158993	.	AB=0.285714;ABP=5.80219;AC=1;AF=0.5;AN=2;AO=2;CIGAR=1X;DP=7;DPB=7;DPRA=0;EPP=3.0103;EPPR=6.91895;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=48.2;NS=1;NUMALT=1;ODDS=7.91247;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=28;QR=169;RO=5;RPL=0;RPP=7.35324;RPPR=13.8677;RPR=2;RUN=1;SAF=1;SAP=3.0103;SAR=1;SRF=1;SRP=6.91895;SRR=4;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:7:5,2:5:169:2:28:-0.55277,0,-10.4001
+chr19	17205973	.	T	C	12243.8	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=406;CIGAR=1X;DP=406;DPB=406;DPRA=0;EPP=14.3276;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=58.4015;MQMR=0;NS=1;NUMALT=1;ODDS=567.441;PAIRED=0.985222;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=14833;QR=0;RO=0;RPL=368;RPP=585.457;RPPR=0;RPR=38;RUN=1;SAF=182;SAP=12.445;SAR=224;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:406:0,406:0:0:406:14833:-1297.85,-122.218,0
+chr2	231456129	.	GGATGGCT	TGATTCAC	54.047	.	AB=0.363636;ABP=4.78696;AC=1;AF=0.5;AN=2;AO=4;CIGAR=1X3M4X;DP=11;DPB=12.375;DPRA=0;EPP=3.0103;EPPR=5.80219;GTI=0;LEN=8;MEANALT=1;MQM=60;MQMR=51.5714;NS=1;NUMALT=1;ODDS=12.4448;PAIRED=1;PAIREDR=0.714286;PAO=0;PQA=0;PQR=134;PRO=4;QA=150;QR=252;RO=7;RPL=0;RPP=11.6962;RPPR=18.2106;RPR=4;RUN=1;SAF=2;SAP=3.0103;SAR=2;SRF=5;SRP=5.80219;SRR=2;TYPE=complex	GT:DP:AD:RO:QR:AO:QA:GL	0/1:11:7,4:7:252:4:150:-9.35048,0,-24.4716
+chr1	189392	.	ACCC	AC	441.589	.	AB=0.294118;ABP=34.305;AC=1;AF=0.5;AN=2;AO=25;CIGAR=1M2D1M;DP=85;DPB=72.5;DPRA=0;EPP=10.0459;EPPR=17.4868;GTI=0;LEN=2;MEANALT=1;MQM=57.64;MQMR=11.8167;NS=1;NUMALT=1;ODDS=15.1558;PAIRED=1;PAIREDR=0.983333;PAO=0;PQA=0;PQR=0;PRO=0;QA=845;QR=2056;RO=60;RPL=11;RPP=3.79203;RPPR=79.5909;RPR=14;RUN=1;SAF=17;SAP=10.0459;SAR=8;SRF=19;SRP=20.5268;SRR=41;TYPE=del	GT:DP:AD:RO:QR:AO:QA:GL	0/1:85:60,25:60:2056:25:845:-47.6855,0,-14.332
+chr1	1758687	.	AACA	AACACA	483.954	.	AB=0.469388;ABP=3.40914;AC=1;AF=0.5;AN=2;AO=23;CIGAR=1M2I3M;DP=49;DPB=60.5;DPRA=0;EPP=44.6459;EPPR=15.0369;GTI=0;LEN=2;MEANALT=1;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=111.434;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=814;QR=931;RO=26;RPL=13;RPP=3.86001;RPPR=4.34659;RPR=10;RUN=1;SAF=9;SAP=5.3706;SAR=14;SRF=10;SRP=6.01695;SRR=16;TYPE=ins	GT:DP:AD:RO:QR:AO:QA:GL	0/1:49:26,23:26:931:23:814:-58.8184,0,-69.3497
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/Freebayes_two-variants.vcf	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,517 @@
+##fileformat=VCFv4.2									
+##fileDate=20180518									
+##source=freeBayes v1.1.0-46-g8d2b3a0-dirty									
+##reference=/panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa									
+"##contig=<ID=chr1,length=248956422>"									
+"##contig=<ID=chr10,length=133797422>"									
+"##contig=<ID=chr11,length=135086622>"									
+"##contig=<ID=chr11_KI270721v1_random,length=100316>"									
+"##contig=<ID=chr12,length=133275309>"									
+"##contig=<ID=chr13,length=114364328>"									
+"##contig=<ID=chr14,length=107043718>"									
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+"##contig=<ID=chr19_KI270916v1_alt,length=184516>"									
+"##contig=<ID=chr19_KI270917v1_alt,length=190932>"									
+"##contig=<ID=chr19_KI270918v1_alt,length=123111>"									
+"##contig=<ID=chr19_KI270919v1_alt,length=170701>"									
+"##contig=<ID=chr19_KI270920v1_alt,length=198005>"									
+"##contig=<ID=chr19_KI270921v1_alt,length=282224>"									
+"##contig=<ID=chr19_KI270922v1_alt,length=187935>"									
+"##contig=<ID=chr19_KI270923v1_alt,length=189352>"									
+"##contig=<ID=chr3_KI270924v1_alt,length=166540>"									
+"##contig=<ID=chr4_KI270925v1_alt,length=555799>"									
+"##contig=<ID=chr6_GL000252v2_alt,length=4604811>"									
+"##contig=<ID=chr8_KI270926v1_alt,length=229282>"									
+"##contig=<ID=chr11_KI270927v1_alt,length=218612>"									
+"##contig=<ID=chr19_GL949748v2_alt,length=1064304>"									
+"##contig=<ID=chr22_KI270928v1_alt,length=176103>"									
+"##contig=<ID=chr19_KI270929v1_alt,length=186203>"									
+"##contig=<ID=chr19_KI270930v1_alt,length=200773>"									
+"##contig=<ID=chr19_KI270931v1_alt,length=170148>"									
+"##contig=<ID=chr19_KI270932v1_alt,length=215732>"									
+"##contig=<ID=chr19_KI270933v1_alt,length=170537>"									
+"##contig=<ID=chr19_GL000209v2_alt,length=177381>"									
+"##contig=<ID=chr3_KI270934v1_alt,length=163458>"									
+"##contig=<ID=chr6_GL000253v2_alt,length=4677643>"									
+"##contig=<ID=chr19_GL949749v2_alt,length=1091841>"									
+"##contig=<ID=chr3_KI270935v1_alt,length=197351>"									
+"##contig=<ID=chr6_GL000254v2_alt,length=4827813>"									
+"##contig=<ID=chr19_GL949750v2_alt,length=1066390>"									
+"##contig=<ID=chr3_KI270936v1_alt,length=164170>"									
+"##contig=<ID=chr6_GL000255v2_alt,length=4606388>"									
+"##contig=<ID=chr19_GL949751v2_alt,length=1002683>"									
+"##contig=<ID=chr3_KI270937v1_alt,length=165607>"									
+"##contig=<ID=chr6_GL000256v2_alt,length=4929269>"									
+"##contig=<ID=chr19_GL949752v1_alt,length=987100>"									
+"##contig=<ID=chr6_KI270758v1_alt,length=76752>"									
+"##contig=<ID=chr19_GL949753v2_alt,length=796479>"									
+"##contig=<ID=chr19_KI270938v1_alt,length=1066800>"									
+"##contig=<ID=chrM,length=16569>"									
+"##contig=<ID=chrUn_KI270302v1,length=2274>"									
+"##contig=<ID=chrUn_KI270304v1,length=2165>"									
+"##contig=<ID=chrUn_KI270303v1,length=1942>"									
+"##contig=<ID=chrUn_KI270305v1,length=1472>"									
+"##contig=<ID=chrUn_KI270322v1,length=21476>"									
+"##contig=<ID=chrUn_KI270320v1,length=4416>"									
+"##contig=<ID=chrUn_KI270310v1,length=1201>"									
+"##contig=<ID=chrUn_KI270316v1,length=1444>"									
+"##contig=<ID=chrUn_KI270315v1,length=2276>"									
+"##contig=<ID=chrUn_KI270312v1,length=998>"									
+"##contig=<ID=chrUn_KI270311v1,length=12399>"									
+"##contig=<ID=chrUn_KI270317v1,length=37690>"									
+"##contig=<ID=chrUn_KI270412v1,length=1179>"									
+"##contig=<ID=chrUn_KI270411v1,length=2646>"									
+"##contig=<ID=chrUn_KI270414v1,length=2489>"									
+"##contig=<ID=chrUn_KI270419v1,length=1029>"									
+"##contig=<ID=chrUn_KI270418v1,length=2145>"									
+"##contig=<ID=chrUn_KI270420v1,length=2321>"									
+"##contig=<ID=chrUn_KI270424v1,length=2140>"									
+"##contig=<ID=chrUn_KI270417v1,length=2043>"									
+"##contig=<ID=chrUn_KI270422v1,length=1445>"									
+"##contig=<ID=chrUn_KI270423v1,length=981>"									
+"##contig=<ID=chrUn_KI270425v1,length=1884>"									
+"##contig=<ID=chrUn_KI270429v1,length=1361>"									
+"##contig=<ID=chrUn_KI270442v1,length=392061>"									
+"##contig=<ID=chrUn_KI270466v1,length=1233>"									
+"##contig=<ID=chrUn_KI270465v1,length=1774>"									
+"##contig=<ID=chrUn_KI270467v1,length=3920>"									
+"##contig=<ID=chrUn_KI270435v1,length=92983>"									
+"##contig=<ID=chrUn_KI270438v1,length=112505>"									
+"##contig=<ID=chrUn_KI270468v1,length=4055>"									
+"##contig=<ID=chrUn_KI270510v1,length=2415>"									
+"##contig=<ID=chrUn_KI270509v1,length=2318>"									
+"##contig=<ID=chrUn_KI270518v1,length=2186>"									
+"##contig=<ID=chrUn_KI270508v1,length=1951>"									
+"##contig=<ID=chrUn_KI270516v1,length=1300>"									
+"##contig=<ID=chrUn_KI270512v1,length=22689>"									
+"##contig=<ID=chrUn_KI270519v1,length=138126>"									
+"##contig=<ID=chrUn_KI270522v1,length=5674>"									
+"##contig=<ID=chrUn_KI270511v1,length=8127>"									
+"##contig=<ID=chrUn_KI270515v1,length=6361>"									
+"##contig=<ID=chrUn_KI270507v1,length=5353>"									
+"##contig=<ID=chrUn_KI270517v1,length=3253>"									
+"##contig=<ID=chrUn_KI270529v1,length=1899>"									
+"##contig=<ID=chrUn_KI270528v1,length=2983>"									
+"##contig=<ID=chrUn_KI270530v1,length=2168>"									
+"##contig=<ID=chrUn_KI270539v1,length=993>"									
+"##contig=<ID=chrUn_KI270538v1,length=91309>"									
+"##contig=<ID=chrUn_KI270544v1,length=1202>"									
+"##contig=<ID=chrUn_KI270548v1,length=1599>"									
+"##contig=<ID=chrUn_KI270583v1,length=1400>"									
+"##contig=<ID=chrUn_KI270587v1,length=2969>"									
+"##contig=<ID=chrUn_KI270580v1,length=1553>"									
+"##contig=<ID=chrUn_KI270581v1,length=7046>"									
+"##contig=<ID=chrUn_KI270579v1,length=31033>"									
+"##contig=<ID=chrUn_KI270589v1,length=44474>"									
+"##contig=<ID=chrUn_KI270590v1,length=4685>"									
+"##contig=<ID=chrUn_KI270584v1,length=4513>"									
+"##contig=<ID=chrUn_KI270582v1,length=6504>"									
+"##contig=<ID=chrUn_KI270588v1,length=6158>"									
+"##contig=<ID=chrUn_KI270593v1,length=3041>"									
+"##contig=<ID=chrUn_KI270591v1,length=5796>"									
+"##contig=<ID=chrUn_KI270330v1,length=1652>"									
+"##contig=<ID=chrUn_KI270329v1,length=1040>"									
+"##contig=<ID=chrUn_KI270334v1,length=1368>"									
+"##contig=<ID=chrUn_KI270333v1,length=2699>"									
+"##contig=<ID=chrUn_KI270335v1,length=1048>"									
+"##contig=<ID=chrUn_KI270338v1,length=1428>"									
+"##contig=<ID=chrUn_KI270340v1,length=1428>"									
+"##contig=<ID=chrUn_KI270336v1,length=1026>"									
+"##contig=<ID=chrUn_KI270337v1,length=1121>"									
+"##contig=<ID=chrUn_KI270363v1,length=1803>"									
+"##contig=<ID=chrUn_KI270364v1,length=2855>"									
+"##contig=<ID=chrUn_KI270362v1,length=3530>"									
+"##contig=<ID=chrUn_KI270366v1,length=8320>"									
+"##contig=<ID=chrUn_KI270378v1,length=1048>"									
+"##contig=<ID=chrUn_KI270379v1,length=1045>"									
+"##contig=<ID=chrUn_KI270389v1,length=1298>"									
+"##contig=<ID=chrUn_KI270390v1,length=2387>"									
+"##contig=<ID=chrUn_KI270387v1,length=1537>"									
+"##contig=<ID=chrUn_KI270395v1,length=1143>"									
+"##contig=<ID=chrUn_KI270396v1,length=1880>"									
+"##contig=<ID=chrUn_KI270388v1,length=1216>"									
+"##contig=<ID=chrUn_KI270394v1,length=970>"									
+"##contig=<ID=chrUn_KI270386v1,length=1788>"									
+"##contig=<ID=chrUn_KI270391v1,length=1484>"									
+"##contig=<ID=chrUn_KI270383v1,length=1750>"									
+"##contig=<ID=chrUn_KI270393v1,length=1308>"									
+"##contig=<ID=chrUn_KI270384v1,length=1658>"									
+"##contig=<ID=chrUn_KI270392v1,length=971>"									
+"##contig=<ID=chrUn_KI270381v1,length=1930>"									
+"##contig=<ID=chrUn_KI270385v1,length=990>"									
+"##contig=<ID=chrUn_KI270382v1,length=4215>"									
+"##contig=<ID=chrUn_KI270376v1,length=1136>"									
+"##contig=<ID=chrUn_KI270374v1,length=2656>"									
+"##contig=<ID=chrUn_KI270372v1,length=1650>"									
+"##contig=<ID=chrUn_KI270373v1,length=1451>"									
+"##contig=<ID=chrUn_KI270375v1,length=2378>"									
+"##contig=<ID=chrUn_KI270371v1,length=2805>"									
+"##contig=<ID=chrUn_KI270448v1,length=7992>"									
+"##contig=<ID=chrUn_KI270521v1,length=7642>"									
+"##contig=<ID=chrUn_GL000195v1,length=182896>"									
+"##contig=<ID=chrUn_GL000219v1,length=179198>"									
+"##contig=<ID=chrUn_GL000220v1,length=161802>"									
+"##contig=<ID=chrUn_GL000224v1,length=179693>"									
+"##contig=<ID=chrUn_KI270741v1,length=157432>"									
+"##contig=<ID=chrUn_GL000226v1,length=15008>"									
+"##contig=<ID=chrUn_GL000213v1,length=164239>"									
+"##contig=<ID=chrUn_KI270743v1,length=210658>"									
+"##contig=<ID=chrUn_KI270744v1,length=168472>"									
+"##contig=<ID=chrUn_KI270745v1,length=41891>"									
+"##contig=<ID=chrUn_KI270746v1,length=66486>"									
+"##contig=<ID=chrUn_KI270747v1,length=198735>"									
+"##contig=<ID=chrUn_KI270748v1,length=93321>"									
+"##contig=<ID=chrUn_KI270749v1,length=158759>"									
+"##contig=<ID=chrUn_KI270750v1,length=148850>"									
+"##contig=<ID=chrUn_KI270751v1,length=150742>"									
+"##contig=<ID=chrUn_KI270752v1,length=27745>"									
+"##contig=<ID=chrUn_KI270753v1,length=62944>"									
+"##contig=<ID=chrUn_KI270754v1,length=40191>"									
+"##contig=<ID=chrUn_KI270755v1,length=36723>"									
+"##contig=<ID=chrUn_KI270756v1,length=79590>"									
+"##contig=<ID=chrUn_KI270757v1,length=71251>"									
+"##contig=<ID=chrUn_GL000214v1,length=137718>"									
+"##contig=<ID=chrUn_KI270742v1,length=186739>"									
+"##contig=<ID=chrUn_GL000216v2,length=176608>"									
+"##contig=<ID=chrUn_GL000218v1,length=161147>"									
+"##contig=<ID=chrX,length=156040895>"									
+"##contig=<ID=chrY,length=57227415>"									
+"##contig=<ID=chrY_KI270740v1_random,length=37240>"									
+##phasing=none									
+"##commandline=""freebayes --region chrY_KI270740v1_random:0..37240 --bam b_0.bam --fasta-reference /panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa --vcf ./vcf_output/part_chrY_KI270740v1_random:0..37240.vcf"""									
+"##INFO=<ID=NS,Number=1,Type=Integer,Description=""Number of samples with data"">"									
+"##INFO=<ID=DP,Number=1,Type=Integer,Description=""Total read depth at the locus"">"									
+"##INFO=<ID=DPB,Number=1,Type=Float,Description=""Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype"">"									
+"##INFO=<ID=AC,Number=A,Type=Integer,Description=""Total number of alternate alleles in called genotypes"">"									
+"##INFO=<ID=AN,Number=1,Type=Integer,Description=""Total number of alleles in called genotypes"">"									
+"##INFO=<ID=AF,Number=A,Type=Float,Description=""Estimated allele frequency in the range (0,1]"">"									
+"##INFO=<ID=RO,Number=1,Type=Integer,Description=""Count of full observations of the reference haplotype."">"									
+"##INFO=<ID=AO,Number=A,Type=Integer,Description=""Count of full observations of this alternate haplotype."">"									
+"##INFO=<ID=PRO,Number=1,Type=Float,Description=""Reference allele observation count, with partial observations recorded fractionally"">"									
+"##INFO=<ID=PAO,Number=A,Type=Float,Description=""Alternate allele observations, with partial observations recorded fractionally"">"									
+"##INFO=<ID=QR,Number=1,Type=Integer,Description=""Reference allele quality sum in phred"">"									
+"##INFO=<ID=QA,Number=A,Type=Integer,Description=""Alternate allele quality sum in phred"">"									
+"##INFO=<ID=PQR,Number=1,Type=Float,Description=""Reference allele quality sum in phred for partial observations"">"									
+"##INFO=<ID=PQA,Number=A,Type=Float,Description=""Alternate allele quality sum in phred for partial observations"">"									
+"##INFO=<ID=SRF,Number=1,Type=Integer,Description=""Number of reference observations on the forward strand"">"									
+"##INFO=<ID=SRR,Number=1,Type=Integer,Description=""Number of reference observations on the reverse strand"">"									
+"##INFO=<ID=SAF,Number=A,Type=Integer,Description=""Number of alternate observations on the forward strand"">"									
+"##INFO=<ID=SAR,Number=A,Type=Integer,Description=""Number of alternate observations on the reverse strand"">"									
+"##INFO=<ID=SRP,Number=1,Type=Float,Description=""Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality"">"									
+"##INFO=<ID=SAP,Number=A,Type=Float,Description=""Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality"">"									
+"##INFO=<ID=AB,Number=A,Type=Float,Description=""Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous"">"									
+"##INFO=<ID=ABP,Number=A,Type=Float,Description=""Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality"">"									
+"##INFO=<ID=RUN,Number=A,Type=Integer,Description=""Run length: the number of consecutive repeats of the alternate allele in the reference genome"">"									
+"##INFO=<ID=RPP,Number=A,Type=Float,Description=""Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality"">"									
+"##INFO=<ID=RPPR,Number=1,Type=Float,Description=""Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality"">"									
+"##INFO=<ID=RPL,Number=A,Type=Float,Description=""Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele"">"									
+"##INFO=<ID=RPR,Number=A,Type=Float,Description=""Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele"">"									
+"##INFO=<ID=EPP,Number=A,Type=Float,Description=""End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality"">"									
+"##INFO=<ID=EPPR,Number=1,Type=Float,Description=""End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality"">"									
+"##INFO=<ID=DPRA,Number=A,Type=Float,Description=""Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without."">"									
+"##INFO=<ID=ODDS,Number=1,Type=Float,Description=""The log odds ratio of the best genotype combination to the second-best."">"									
+"##INFO=<ID=GTI,Number=1,Type=Integer,Description=""Number of genotyping iterations required to reach convergence or bailout."">"									
+"##INFO=<ID=TYPE,Number=A,Type=String,Description=""The type of allele, either snp, mnp, ins, del, or complex."">"									
+"##INFO=<ID=CIGAR,Number=A,Type=String,Description=""The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR."">"									
+"##INFO=<ID=NUMALT,Number=1,Type=Integer,Description=""Number of unique non-reference alleles in called genotypes at this position."">"									
+"##INFO=<ID=MEANALT,Number=A,Type=Float,Description=""Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles."">"									
+"##INFO=<ID=LEN,Number=A,Type=Integer,Description=""allele length"">"									
+"##INFO=<ID=MQM,Number=A,Type=Float,Description=""Mean mapping quality of observed alternate alleles"">"									
+"##INFO=<ID=MQMR,Number=1,Type=Float,Description=""Mean mapping quality of observed reference alleles"">"									
+"##INFO=<ID=PAIRED,Number=A,Type=Float,Description=""Proportion of observed alternate alleles which are supported by properly paired read fragments"">"									
+"##INFO=<ID=PAIREDR,Number=1,Type=Float,Description=""Proportion of observed reference alleles which are supported by properly paired read fragments"">"									
+"##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description=""Minimum depth in gVCF output block."">"									
+"##INFO=<ID=END,Number=1,Type=Integer,Description=""Last position (inclusive) in gVCF output record."">"									
+"##FORMAT=<ID=GT,Number=1,Type=String,Description=""Genotype"">"									
+"##FORMAT=<ID=GQ,Number=1,Type=Float,Description=""Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype"">"									
+"##FORMAT=<ID=GL,Number=G,Type=Float,Description=""Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy"">"									
+"##FORMAT=<ID=DP,Number=1,Type=Integer,Description=""Read Depth"">"									
+"##FORMAT=<ID=AD,Number=R,Type=Integer,Description=""Number of observation for each allele"">"									
+"##FORMAT=<ID=RO,Number=1,Type=Integer,Description=""Reference allele observation count"">"									
+"##FORMAT=<ID=QR,Number=1,Type=Integer,Description=""Sum of quality of the reference observations"">"									
+"##FORMAT=<ID=AO,Number=A,Type=Integer,Description=""Alternate allele observation count"">"									
+"##FORMAT=<ID=QA,Number=A,Type=Integer,Description=""Sum of quality of the alternate observations"">"									
+"##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description=""Minimum depth in gVCF output block."">"									
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	unknown
+chr1	156701052	.	C	T	122.853	.	AB=0.4;ABP=4.74748;AC=1;AF=0.5;AN=2;AO=8;CIGAR=1X;DP=20;DPB=20;DPRA=0;EPP=4.09604;EPPR=4.45795;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=11.0181;PAIRED=1;PAIREDR=0.833333;PAO=0;PQA=0;PQR=0;PRO=0;QA=255;QR=217;RO=6;RPL=0;RPP=20.3821;RPPR=4.45795;RPR=8;RUN=1;SAF=5;SAP=4.09604;SAR=3;SRF=6;SRP=16.0391;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	"0/1:20:6,8:6:217:8:255:-18.7505,0,-15.3493"
+chr19	18856059	.	C	T	10269.5	.	AB=0.248844;ABP=1306.46;AC=1;AF=0.5;AN=2;AO=592;CIGAR=1X;DP=2379;DPB=2379;DPRA=0;EPP=30.139;EPPR=172.262;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=59.9339;NS=1;NUMALT=1;ODDS=2364.65;PAIRED=0.991554;PAIREDR=0.983754;PAO=0;PQA=0;PQR=0;PRO=0;QA=21546;QR=64865;RO=1785;RPL=120;RPP=457.494;RPPR=1043.89;RPR=472;RUN=1;SAF=303;SAP=3.72923;SAR=289;SRF=873;SRP=4.86061;SRR=912;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	"0/1:2379:1785,592:1785:64865:592:21546:-1222.54,0,-5112.92"
\ No newline at end of file
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/MCF7_proBed.bed	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,17 @@
+chr14	94079127	94079178	ADVSAWKDLFVPGPVLR	255	-	94079127	94079178	0	1	51	0
+chr14	94079127	94079178	ADVSAWKDLFVPGPVLR	255	-	94079127	94079178	0	1	51	0
+chr19	18856027	18856078	EAIDSPVSFLVLHNQIR	255	+	18856027	18856078	0	1	51	0
+chr12	110339607	110339637	EWGSGSDILR	255	+	110339607	110339637	0	1	30	0
+chr12	110339607	110339637	EWGSGSDILR	255	+	110339607	110339637	0	1	30	0
+chr14	102083930	102083972	GVVDSENLPLNISR	255	-	102083930	102083972	0	1	42	0
+chr14	102083930	102083972	GVVDSENLPLNISR	255	-	102083930	102083972	0	1	42	0
+chr19	17205300	17206022	IQSHCSYTYGRMGEPGAEPGHFGVCVDSLTSDK	255	+	17205300	17206022	0	2	36,63	0,659
+chr2	231457346	231457474	NSTWSDDSR	255	-	231457346	231457474	0	2	-168,195	0,-67
+chr17	82082586	82082643	QGVQVQVSTSNINSLEGAR	255	-	82082586	82082643	0	1	57	0
+chr17	82082586	82082643	QGVQVQVSTSNINSLEGAR	255	-	82082586	82082643	0	1	57	0
+chr12	6561014	6561056	STGVILANDANAER	255	-	6561014	6561056	0	1	42	0
+chr12	6561014	6561056	STGVILANDANAER	255	-	6561014	6561056	0	1	42	0
+chr12	6561014	6561056	STGVILANDANAER	255	-	6561014	6561056	0	1	42	0
+chr12	6561014	6561056	STGVILANDANAER	255	-	6561014	6561056	0	1	42	0
+chr2	231457113	231457124	TLQHVLGESK	255	-	231457113	231457124	0	2	-481,511	0,-500
+chr17	2711607	2711658	VIKTDELPAAAPADSAR	255	-	2711607	2711658	0	1	51	0
--- a/test-data/[PepPointer].bed	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,20 +0,0 @@
-chr14	94079127	94079178	ADVSAWKDLFVPGPVLR	255	-	CDS
-chr14	94079127	94079178	ADVSAWKDLFVPGPVLR	255	-	CDS
-chr14	102011973	102012027	ALESLEGVEGVAHIIDPK	255	+	CDS
-chr19	18856027	18856078	EAIDSPVSFLVLHNQIR	255	+	CDS
-chr12	110339607	110339637	EWGSGSDILR	255	+	CDS
-chr12	110339607	110339637	EWGSGSDILR	255	+	CDS
-chr14	102083930	102083972	GVVDSENLPLNISR	255	-	CDS
-chr14	102083930	102083972	GVVDSENLPLNISR	255	-	CDS
-chr19	17205300	17206022	IQSHCSYTYGRMGEPGAEPGHFGVCVDSLTSDK	255	+	SpliceJunction
-chr1	156705410	156705446	MPNFSGNWEIIR	255	-	CDS
-chr1	156705410	156705446	MPNFSGNWEIIR	255	-	CDS
-chr2	231457346	231457474	NSTWSDDSR	255	-	SpliceJunction
-chr17	82082586	82082643	QGVQVQVSTSNINSLEGAR	255	-	CDS
-chr17	82082586	82082643	QGVQVQVSTSNINSLEGAR	255	-	CDS
-chr12	6561014	6561056	STGVILANDANAER	255	-	CDS
-chr12	6561014	6561056	STGVILANDANAER	255	-	CDS
-chr12	6561014	6561056	STGVILANDANAER	255	-	CDS
-chr12	6561014	6561056	STGVILANDANAER	255	-	CDS
-chr2	231457113	231457124	TLQHVLGESK	255	-	SpliceJunction
-chr17	2711607	2711658	VIKTDELPAAAPADSAR	255	-	CDS
--- a/test-data/[VCF-BEDintersect__on_data_65_and_data_6].vcf	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,526 +0,0 @@
-##fileformat=VCFv4.2
-##fileDate=20180504
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-##contig=<ID=chr4_KI270896v1_alt,length=378547>
-##contig=<ID=chr5_KI270897v1_alt,length=1144418>
-##contig=<ID=chr5_KI270898v1_alt,length=130957>
-##contig=<ID=chr6_GL000251v2_alt,length=4795265>
-##contig=<ID=chr7_KI270899v1_alt,length=190869>
-##contig=<ID=chr8_KI270901v1_alt,length=136959>
-##contig=<ID=chr8_KI270900v1_alt,length=318687>
-##contig=<ID=chr11_KI270902v1_alt,length=106711>
-##contig=<ID=chr11_KI270903v1_alt,length=214625>
-##contig=<ID=chr12_KI270904v1_alt,length=572349>
-##contig=<ID=chr15_KI270906v1_alt,length=196384>
-##contig=<ID=chr15_KI270905v1_alt,length=5161414>
-##contig=<ID=chr17_KI270907v1_alt,length=137721>
-##contig=<ID=chr17_KI270910v1_alt,length=157099>
-##contig=<ID=chr17_KI270909v1_alt,length=325800>
-##contig=<ID=chr17_JH159148v1_alt,length=88070>
-##contig=<ID=chr17_KI270908v1_alt,length=1423190>
-##contig=<ID=chr18_KI270912v1_alt,length=174061>
-##contig=<ID=chr18_KI270911v1_alt,length=157710>
-##contig=<ID=chr19_GL949747v2_alt,length=729520>
-##contig=<ID=chr22_KB663609v1_alt,length=74013>
-##contig=<ID=chrX_KI270913v1_alt,length=274009>
-##contig=<ID=chr19_KI270914v1_alt,length=205194>
-##contig=<ID=chr19_KI270915v1_alt,length=170665>
-##contig=<ID=chr19_KI270916v1_alt,length=184516>
-##contig=<ID=chr19_KI270917v1_alt,length=190932>
-##contig=<ID=chr19_KI270918v1_alt,length=123111>
-##contig=<ID=chr19_KI270919v1_alt,length=170701>
-##contig=<ID=chr19_KI270920v1_alt,length=198005>
-##contig=<ID=chr19_KI270921v1_alt,length=282224>
-##contig=<ID=chr19_KI270922v1_alt,length=187935>
-##contig=<ID=chr19_KI270923v1_alt,length=189352>
-##contig=<ID=chr3_KI270924v1_alt,length=166540>
-##contig=<ID=chr4_KI270925v1_alt,length=555799>
-##contig=<ID=chr6_GL000252v2_alt,length=4604811>
-##contig=<ID=chr8_KI270926v1_alt,length=229282>
-##contig=<ID=chr11_KI270927v1_alt,length=218612>
-##contig=<ID=chr19_GL949748v2_alt,length=1064304>
-##contig=<ID=chr22_KI270928v1_alt,length=176103>
-##contig=<ID=chr19_KI270929v1_alt,length=186203>
-##contig=<ID=chr19_KI270930v1_alt,length=200773>
-##contig=<ID=chr19_KI270931v1_alt,length=170148>
-##contig=<ID=chr19_KI270932v1_alt,length=215732>
-##contig=<ID=chr19_KI270933v1_alt,length=170537>
-##contig=<ID=chr19_GL000209v2_alt,length=177381>
-##contig=<ID=chr3_KI270934v1_alt,length=163458>
-##contig=<ID=chr6_GL000253v2_alt,length=4677643>
-##contig=<ID=chr19_GL949749v2_alt,length=1091841>
-##contig=<ID=chr3_KI270935v1_alt,length=197351>
-##contig=<ID=chr6_GL000254v2_alt,length=4827813>
-##contig=<ID=chr19_GL949750v2_alt,length=1066390>
-##contig=<ID=chr3_KI270936v1_alt,length=164170>
-##contig=<ID=chr6_GL000255v2_alt,length=4606388>
-##contig=<ID=chr19_GL949751v2_alt,length=1002683>
-##contig=<ID=chr3_KI270937v1_alt,length=165607>
-##contig=<ID=chr6_GL000256v2_alt,length=4929269>
-##contig=<ID=chr19_GL949752v1_alt,length=987100>
-##contig=<ID=chr6_KI270758v1_alt,length=76752>
-##contig=<ID=chr19_GL949753v2_alt,length=796479>
-##contig=<ID=chr19_KI270938v1_alt,length=1066800>
-##contig=<ID=chrM,length=16569>
-##contig=<ID=chrUn_KI270302v1,length=2274>
-##contig=<ID=chrUn_KI270304v1,length=2165>
-##contig=<ID=chrUn_KI270303v1,length=1942>
-##contig=<ID=chrUn_KI270305v1,length=1472>
-##contig=<ID=chrUn_KI270322v1,length=21476>
-##contig=<ID=chrUn_KI270320v1,length=4416>
-##contig=<ID=chrUn_KI270310v1,length=1201>
-##contig=<ID=chrUn_KI270316v1,length=1444>
-##contig=<ID=chrUn_KI270315v1,length=2276>
-##contig=<ID=chrUn_KI270312v1,length=998>
-##contig=<ID=chrUn_KI270311v1,length=12399>
-##contig=<ID=chrUn_KI270317v1,length=37690>
-##contig=<ID=chrUn_KI270412v1,length=1179>
-##contig=<ID=chrUn_KI270411v1,length=2646>
-##contig=<ID=chrUn_KI270414v1,length=2489>
-##contig=<ID=chrUn_KI270419v1,length=1029>
-##contig=<ID=chrUn_KI270418v1,length=2145>
-##contig=<ID=chrUn_KI270420v1,length=2321>
-##contig=<ID=chrUn_KI270424v1,length=2140>
-##contig=<ID=chrUn_KI270417v1,length=2043>
-##contig=<ID=chrUn_KI270422v1,length=1445>
-##contig=<ID=chrUn_KI270423v1,length=981>
-##contig=<ID=chrUn_KI270425v1,length=1884>
-##contig=<ID=chrUn_KI270429v1,length=1361>
-##contig=<ID=chrUn_KI270442v1,length=392061>
-##contig=<ID=chrUn_KI270466v1,length=1233>
-##contig=<ID=chrUn_KI270465v1,length=1774>
-##contig=<ID=chrUn_KI270467v1,length=3920>
-##contig=<ID=chrUn_KI270435v1,length=92983>
-##contig=<ID=chrUn_KI270438v1,length=112505>
-##contig=<ID=chrUn_KI270468v1,length=4055>
-##contig=<ID=chrUn_KI270510v1,length=2415>
-##contig=<ID=chrUn_KI270509v1,length=2318>
-##contig=<ID=chrUn_KI270518v1,length=2186>
-##contig=<ID=chrUn_KI270508v1,length=1951>
-##contig=<ID=chrUn_KI270516v1,length=1300>
-##contig=<ID=chrUn_KI270512v1,length=22689>
-##contig=<ID=chrUn_KI270519v1,length=138126>
-##contig=<ID=chrUn_KI270522v1,length=5674>
-##contig=<ID=chrUn_KI270511v1,length=8127>
-##contig=<ID=chrUn_KI270515v1,length=6361>
-##contig=<ID=chrUn_KI270507v1,length=5353>
-##contig=<ID=chrUn_KI270517v1,length=3253>
-##contig=<ID=chrUn_KI270529v1,length=1899>
-##contig=<ID=chrUn_KI270528v1,length=2983>
-##contig=<ID=chrUn_KI270530v1,length=2168>
-##contig=<ID=chrUn_KI270539v1,length=993>
-##contig=<ID=chrUn_KI270538v1,length=91309>
-##contig=<ID=chrUn_KI270544v1,length=1202>
-##contig=<ID=chrUn_KI270548v1,length=1599>
-##contig=<ID=chrUn_KI270583v1,length=1400>
-##contig=<ID=chrUn_KI270587v1,length=2969>
-##contig=<ID=chrUn_KI270580v1,length=1553>
-##contig=<ID=chrUn_KI270581v1,length=7046>
-##contig=<ID=chrUn_KI270579v1,length=31033>
-##contig=<ID=chrUn_KI270589v1,length=44474>
-##contig=<ID=chrUn_KI270590v1,length=4685>
-##contig=<ID=chrUn_KI270584v1,length=4513>
-##contig=<ID=chrUn_KI270582v1,length=6504>
-##contig=<ID=chrUn_KI270588v1,length=6158>
-##contig=<ID=chrUn_KI270593v1,length=3041>
-##contig=<ID=chrUn_KI270591v1,length=5796>
-##contig=<ID=chrUn_KI270330v1,length=1652>
-##contig=<ID=chrUn_KI270329v1,length=1040>
-##contig=<ID=chrUn_KI270334v1,length=1368>
-##contig=<ID=chrUn_KI270333v1,length=2699>
-##contig=<ID=chrUn_KI270335v1,length=1048>
-##contig=<ID=chrUn_KI270338v1,length=1428>
-##contig=<ID=chrUn_KI270340v1,length=1428>
-##contig=<ID=chrUn_KI270336v1,length=1026>
-##contig=<ID=chrUn_KI270337v1,length=1121>
-##contig=<ID=chrUn_KI270363v1,length=1803>
-##contig=<ID=chrUn_KI270364v1,length=2855>
-##contig=<ID=chrUn_KI270362v1,length=3530>
-##contig=<ID=chrUn_KI270366v1,length=8320>
-##contig=<ID=chrUn_KI270378v1,length=1048>
-##contig=<ID=chrUn_KI270379v1,length=1045>
-##contig=<ID=chrUn_KI270389v1,length=1298>
-##contig=<ID=chrUn_KI270390v1,length=2387>
-##contig=<ID=chrUn_KI270387v1,length=1537>
-##contig=<ID=chrUn_KI270395v1,length=1143>
-##contig=<ID=chrUn_KI270396v1,length=1880>
-##contig=<ID=chrUn_KI270388v1,length=1216>
-##contig=<ID=chrUn_KI270394v1,length=970>
-##contig=<ID=chrUn_KI270386v1,length=1788>
-##contig=<ID=chrUn_KI270391v1,length=1484>
-##contig=<ID=chrUn_KI270383v1,length=1750>
-##contig=<ID=chrUn_KI270393v1,length=1308>
-##contig=<ID=chrUn_KI270384v1,length=1658>
-##contig=<ID=chrUn_KI270392v1,length=971>
-##contig=<ID=chrUn_KI270381v1,length=1930>
-##contig=<ID=chrUn_KI270385v1,length=990>
-##contig=<ID=chrUn_KI270382v1,length=4215>
-##contig=<ID=chrUn_KI270376v1,length=1136>
-##contig=<ID=chrUn_KI270374v1,length=2656>
-##contig=<ID=chrUn_KI270372v1,length=1650>
-##contig=<ID=chrUn_KI270373v1,length=1451>
-##contig=<ID=chrUn_KI270375v1,length=2378>
-##contig=<ID=chrUn_KI270371v1,length=2805>
-##contig=<ID=chrUn_KI270448v1,length=7992>
-##contig=<ID=chrUn_KI270521v1,length=7642>
-##contig=<ID=chrUn_GL000195v1,length=182896>
-##contig=<ID=chrUn_GL000219v1,length=179198>
-##contig=<ID=chrUn_GL000220v1,length=161802>
-##contig=<ID=chrUn_GL000224v1,length=179693>
-##contig=<ID=chrUn_KI270741v1,length=157432>
-##contig=<ID=chrUn_GL000226v1,length=15008>
-##contig=<ID=chrUn_GL000213v1,length=164239>
-##contig=<ID=chrUn_KI270743v1,length=210658>
-##contig=<ID=chrUn_KI270744v1,length=168472>
-##contig=<ID=chrUn_KI270745v1,length=41891>
-##contig=<ID=chrUn_KI270746v1,length=66486>
-##contig=<ID=chrUn_KI270747v1,length=198735>
-##contig=<ID=chrUn_KI270748v1,length=93321>
-##contig=<ID=chrUn_KI270749v1,length=158759>
-##contig=<ID=chrUn_KI270750v1,length=148850>
-##contig=<ID=chrUn_KI270751v1,length=150742>
-##contig=<ID=chrUn_KI270752v1,length=27745>
-##contig=<ID=chrUn_KI270753v1,length=62944>
-##contig=<ID=chrUn_KI270754v1,length=40191>
-##contig=<ID=chrUn_KI270755v1,length=36723>
-##contig=<ID=chrUn_KI270756v1,length=79590>
-##contig=<ID=chrUn_KI270757v1,length=71251>
-##contig=<ID=chrUn_GL000214v1,length=137718>
-##contig=<ID=chrUn_KI270742v1,length=186739>
-##contig=<ID=chrUn_GL000216v2,length=176608>
-##contig=<ID=chrUn_GL000218v1,length=161147>
-##contig=<ID=chrX,length=156040895>
-##contig=<ID=chrY,length=57227415>
-##contig=<ID=chrY_KI270740v1_random,length=37240>
-##phasing=none
-##commandline="freebayes --region chrY_KI270740v1_random:0..37240 --bam b_0.bam --fasta-reference /panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa --vcf ./vcf_output/part_chrY_KI270740v1_random:0..37240.vcf"
-##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
-##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
-##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
-##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
-##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
-##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
-##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
-##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
-##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
-##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
-##INFO=<ID=QR,Number=1,Type=Integer,Description="Reference allele quality sum in phred">
-##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
-##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
-##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
-##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
-##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
-##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
-##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
-##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
-##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
-##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
-##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
-##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
-##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
-##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
-##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
-##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
-##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
-##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
-##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
-##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
-##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
-##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
-##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
-##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
-##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
-##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
-##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
-##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
-##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
-##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
-##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
-##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
-##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
-##FORMAT=<ID=GQ,Number=1,Type=Float,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
-##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
-##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
-##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
-##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
-##FORMAT=<ID=QR,Number=1,Type=Integer,Description="Sum of quality of the reference observations">
-##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
-##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
-##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
-#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	unknown
-chr1	156705422	.	T	C	125181	.	AB=0.318515;ABP=5157.71;AC=1;AF=0.5;AN=2;AO=5739;CIGAR=1X;DP=18018;DPB=18018;DPRA=0;EPP=283.505;EPPR=1125.27;GTI=0;LEN=1;MEANALT=3;MQM=59.7327;MQMR=59.6874;NS=1;NUMALT=1;ODDS=28824;PAIRED=0.984666;PAIREDR=0.981823;PAO=0;PQA=0;PQR=0;PRO=0;QA=208036;QR=445024;RO=12268;RPL=3614;RPP=841.905;RPPR=1072.42;RPR=2125;RUN=1;SAF=3390;SAP=413.044;SAR=2349;SRF=6908;SRP=427.163;SRR=5360;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:18018:12268,5739:12268:445024:5739:208036:-13208.4,0,-34397.1
-chr12	6561055	.	T	C	14340.8	.	AB=0.235264;ABP=2357.67;AC=1;AF=0.5;AN=2;AO=910;CIGAR=1X;DP=3868;DPB=3868;DPRA=0;EPP=7.21962;EPPR=59.3944;GTI=0;LEN=1;MEANALT=2;MQM=59.9352;MQMR=59.6406;NS=1;NUMALT=1;ODDS=3302.08;PAIRED=0.983516;PAIREDR=0.990186;PAO=0;PQA=0;PQR=0;PRO=0;QA=33224;QR=106496;RO=2955;RPL=107;RPP=1158.94;RPPR=4030.18;RPR=803;RUN=1;SAF=481;SAP=9.46268;SAR=429;SRF=1663;SRP=104.155;SRR=1292;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:3868:2955,910:2955:106496:910:33224:-1821.72,0,-8360.65
-chr12	110339630	.	C	T	48828.1	.	AB=0.268901;ABP=4224.36;AC=1;AF=0.5;AN=2;AO=2447;CIGAR=1X;DP=9100;DPB=9100;DPRA=0;EPP=710.668;EPPR=1883.3;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=11243.1;PAIRED=0.985288;PAIREDR=0.980156;PAO=0;PQA=0;PQR=0;PRO=0;QA=90595;QR=244569;RO=6652;RPL=1094;RPP=62.5381;RPPR=155.737;RPR=1353;RUN=1;SAF=1227;SAP=3.05378;SAR=1220;SRF=3354;SRP=4.03401;SRR=3298;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:9100:6652,2447:6652:244569:2447:90595:-5409.03,0,-19257.6
-chr14	94079142	.	T	C	0	.	AB=0;ABP=0;AC=0;AF=0;AN=2;AO=672;CIGAR=1X;DP=3227;DPB=3227;DPRA=0;EPP=117.219;EPPR=488.229;GTI=0;LEN=1;MEANALT=3;MQM=13.9062;MQMR=8.44728;NS=1;NUMALT=1;ODDS=1413.33;PAIRED=0.995536;PAIREDR=0.994512;PAO=0;PQA=0;PQR=0;PRO=0;QA=24358;QR=92741;RO=2551;RPL=349;RPP=5.1947;RPPR=253.993;RPR=323;RUN=1;SAF=301;SAP=18.844;SAR=371;SRF=1157;SRP=50.8227;SRR=1394;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/0:3227:2551,672:2551:92741:672:24358:0,-455.681,-680.616
-chr14	102011985	.	A	T	12962.3	.	AB=0.301267;ABP=734.044;AC=1;AF=0.5;AN=2;AO=642;CIGAR=1X;DP=2131;DPB=2131;DPRA=0;EPP=6.47383;EPPR=23.6897;GTI=0;LEN=1;MEANALT=3;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=2984.69;PAIRED=0.995327;PAIREDR=0.98117;PAO=0;PQA=0;PQR=0;PRO=0;QA=22490;QR=51005;RO=1487;RPL=362;RPP=25.7533;RPPR=15.6405;RPR=280;RUN=1;SAF=307;SAP=5.66207;SAR=335;SRF=729;SRP=4.23842;SRR=758;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:2131:1487,642:1487:51005:642:22490:-1382.22,0,-3947.19
-chr14	102083954	.	C	T	240809	.	AB=0.203741;ABP=65012.9;AC=1;AF=0.5;AN=2;AO=17374;CIGAR=1X;DP=85275;DPB=85275;DPRA=0;EPP=2106.04;EPPR=12892.8;GTI=0;LEN=1;MEANALT=3;MQM=60;MQMR=60;NS=1;NUMALT=1;ODDS=55448.2;PAIRED=0.982387;PAIREDR=0.980402;PAO=0;PQA=0;PQR=0;PRO=0;QA=637599;QR=2489236;RO=67865;RPL=5766;RPP=4268.59;RPPR=13677.6;RPR=11608;RUN=1;SAF=9064;SAP=74.0657;SAR=8310;SRF=35817;SRP=457.538;SRR=32048;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:85275:67865,17374:67865:2489236:17374:637599:-31686.8,0,-198225
-chr17	82082606	.	C	T	10374.8	.	AB=0.202823;ABP=2937.89;AC=1;AF=0.5;AN=2;AO=776;CIGAR=1X;DP=3826;DPB=3826;DPRA=0;EPP=22.755;EPPR=126.853;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=59.9806;NS=1;NUMALT=1;ODDS=2388.89;PAIRED=0.981959;PAIREDR=0.985569;PAO=0;PQA=0;PQR=0;PRO=0;QA=27982;QR=110520;RO=3049;RPL=338;RPP=30.9932;RPPR=253.452;RPR=438;RUN=1;SAF=422;SAP=15.9496;SAR=354;SRF=1759;SRP=159.665;SRR=1290;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:3826:3049,776:3049:110520:776:27982:-1365.58,0,-8788
-chr19	17205335	.	A	T	0.00158993	.	AB=0.285714;ABP=5.80219;AC=1;AF=0.5;AN=2;AO=2;CIGAR=1X;DP=7;DPB=7;DPRA=0;EPP=3.0103;EPPR=6.91895;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=48.2;NS=1;NUMALT=1;ODDS=7.91247;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=28;QR=169;RO=5;RPL=0;RPP=7.35324;RPPR=13.8677;RPR=2;RUN=1;SAF=1;SAP=3.0103;SAR=1;SRF=1;SRP=6.91895;SRR=4;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:7:5,2:5:169:2:28:-0.55277,0,-10.4001
-chr19	17205444	.	T	C	206.198	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=7;CIGAR=1X;DP=7;DPB=7;DPRA=0;EPP=5.80219;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=14.3092;PAIRED=0.857143;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=249;QR=0;RO=0;RPL=2;RPP=5.80219;RPPR=0;RPR=5;RUN=1;SAF=4;SAP=3.32051;SAR=3;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:7:0,7:0:0:7:249:-22.753,-2.10721,0
-chr19	17205973	.	T	C	12243.8	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=406;CIGAR=1X;DP=406;DPB=406;DPRA=0;EPP=14.3276;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=58.4015;MQMR=0;NS=1;NUMALT=1;ODDS=567.441;PAIRED=0.985222;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=14833;QR=0;RO=0;RPL=368;RPP=585.457;RPPR=0;RPR=38;RUN=1;SAF=182;SAP=12.445;SAR=224;SRF=0;SRP=0;SRR=0;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	1/1:406:0,406:0:0:406:14833:-1297.85,-122.218,0
-chr19	18856059	.	C	T	10269.5	.	AB=0.248844;ABP=1306.46;AC=1;AF=0.5;AN=2;AO=592;CIGAR=1X;DP=2379;DPB=2379;DPRA=0;EPP=30.139;EPPR=174.082;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=59.9339;NS=1;NUMALT=1;ODDS=2364.65;PAIRED=0.991554;PAIREDR=0.983754;PAO=0;PQA=0;PQR=0;PRO=0;QA=21546;QR=64865;RO=1785;RPL=120;RPP=457.494;RPPR=1048.39;RPR=472;RUN=1;SAF=303;SAP=3.72923;SAR=289;SRF=873;SRP=4.86061;SRR=912;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:2379:1785,592:1785:64865:592:21546:-1222.54,0,-5112.92
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/error.tsv	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,12 @@
+#Input Errors Report
+#2018-08-13 15:36:32.358464
+#CRAVAT version: hybrid
+#Analysis done at http://www.cravat.us.
+#Job Id: rsajulga_20180813_113614
+#Input file: Freebayes_two_variants.vcf
+#This report shows errors that occurred in the input.
+#Input coordinate: hg38 genomic.
+#CHASM classifier: Breast
+#For more information on CRAVAT, visit http://www.cravat.us.
+
+Input line number$%$Input line UID$%$Gene$%$Error$%$Input Line
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/gene.tsv	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,15 @@
+#Gene Level Annotation Report
+#2018-08-13 15:36:32.359533
+#CRAVAT version: hybrid
+#Analysis done at http://www.cravat.us.
+#Job Id: rsajulga_20180813_113614
+#Input file: Freebayes_two_variants.vcf
+#This report shows analysis results at gene level.
+#The composite p-value (Stouffer's combined p-value) and composite FDR of a gene show how probable it is to get the same p-value distribution for the gene as that obtained from the input variants by chance.
+#hg38 genomic.
+#Breast
+#For more information on CRAVAT, visit http://www.cravat.us.
+
+HUGO symbol	Number of variants	Sequence ontology	CGC driver class	CGC inheritance	CGC tumor types somatic	CGC tumor types germline	ClinVar disease identifier	ClinVar XRef	Occurrences in COSMIC	COSMIC gene count (tissue)	Number of samples with gene mutated	CHASM gene score	CHASM gene p-value	CHASM gene FDR	VEST gene score (non-silent)	VEST gene p-value	VEST gene FDR	Protein 3D gene	Has a mutation in a TCGA Mutation Cluster	NCI pathway hits	NCI pathway IDs	NCI pathway names	TARGET	CGL driver class
+CRABP2	1	MS							37	upper_aerodigestive_tract(3);large_intestine(9);stomach(4);soft_tissue(3);endometrium(4);lung(3);liver(2);skin(4);NS(1);prostate(1);bone(1);kidney(1);breast(1)	1	0.358	0.4176	1				../MuPIT_Interactive?gm=chr1:156701052		0				
+UPF1	1	MS							267	large_intestine(57);endometrium(18);lung(13);skin(45);meninges(1);kidney(9);thyroid(3);cervix(4);central_nervous_system(7);oesophagus(5);NS(4);upper_aerodigestive_tract(10);biliary_tract(2);stomach(15);soft_tissue(6);urinary_tract(12);breast(11);prostate(7);pancreas(7);haematopoietic_and_lymphoid_tissue(10);ovary(4);bone(2);liver(15)	1	0.63	0.0394	0.1				../MuPIT_Interactive?gm=chr19:18856059		0				
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/noncoding.tsv	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,12 @@
+#Non-coding Variant Report
+#2018-08-13 15:36:32.354693
+#CRAVAT version: hybrid
+#Analysis done at http://www.cravat.us.
+#Job Id: rsajulga_20180813_113614
+#Input file: Freebayes_two_variants.vcf
+#This report shows analysis results at variant level.
+#hg38 genomic.
+#Breast
+#For more information on CRAVAT, visit http://www.cravat.us.
+
+Input line	ID	Chromosome	Position	Strand	Reference base(s)	Alternate base(s)	Sample ID	HUGO symbol	Sequence ontology	Protein sequence change	CHASM p-value	CHASM FDR	ClinVar	COSMIC ID	COSMIC variant count (tissue)	Number of samples with variant	dbSNP	ESP6500 AF (average)	gnomAD AF Total	gnomAD AF African	gnomAD AF American	gnomAD AF Ashkenazi Jewish	gnomAD AF East Asian	gnomAD AF Finnish	gnomAD AF Non-Finnish European	gnomAD AF Other	gnomAD AF South Asian	GWAS NHLBI Key (GRASP)	GWAS PMID (GRASP)	GWAS Phenotype (GRASP)	Protein 3D variant	In TCGA Mutation Cluster	ncRNA Class	ncRNA Name	Pseudogene	Pseudogene Transcript	Repeat Class	Repeat Family	Repeat Name	TARGET	1000 Genomes AF	UTR/Intron	UTR/Intron Gene	UTR/Intron All Transcript	Phred	VCF filters	Zygosity	Alternate reads	Total reads	Variant allele frequency	CGL driver class
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/results/intersected_vcf.vcf	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,516 @@
+##fileformat=VCFv4.2
+##fileDate=20180518
+##source=freeBayes  v1.1.0-46-g8d2b3a0-dirty
+##reference=/panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa
+##contig=<ID=chr1,length=248956422>
+##contig=<ID=chr10,length=133797422>
+##contig=<ID=chr11,length=135086622>
+##contig=<ID=chr11_KI270721v1_random,length=100316>
+##contig=<ID=chr12,length=133275309>
+##contig=<ID=chr13,length=114364328>
+##contig=<ID=chr14,length=107043718>
+##contig=<ID=chr14_GL000009v2_random,length=201709>
+##contig=<ID=chr14_GL000225v1_random,length=211173>
+##contig=<ID=chr14_KI270722v1_random,length=194050>
+##contig=<ID=chr14_GL000194v1_random,length=191469>
+##contig=<ID=chr14_KI270723v1_random,length=38115>
+##contig=<ID=chr14_KI270724v1_random,length=39555>
+##contig=<ID=chr14_KI270725v1_random,length=172810>
+##contig=<ID=chr14_KI270726v1_random,length=43739>
+##contig=<ID=chr15,length=101991189>
+##contig=<ID=chr15_KI270727v1_random,length=448248>
+##contig=<ID=chr16,length=90338345>
+##contig=<ID=chr16_KI270728v1_random,length=1872759>
+##contig=<ID=chr17,length=83257441>
+##contig=<ID=chr17_GL000205v2_random,length=185591>
+##contig=<ID=chr17_KI270729v1_random,length=280839>
+##contig=<ID=chr17_KI270730v1_random,length=112551>
+##contig=<ID=chr18,length=80373285>
+##contig=<ID=chr19,length=58617616>
+##contig=<ID=chr1_KI270706v1_random,length=175055>
+##contig=<ID=chr1_KI270707v1_random,length=32032>
+##contig=<ID=chr1_KI270708v1_random,length=127682>
+##contig=<ID=chr1_KI270709v1_random,length=66860>
+##contig=<ID=chr1_KI270710v1_random,length=40176>
+##contig=<ID=chr1_KI270711v1_random,length=42210>
+##contig=<ID=chr1_KI270712v1_random,length=176043>
+##contig=<ID=chr1_KI270713v1_random,length=40745>
+##contig=<ID=chr1_KI270714v1_random,length=41717>
+##contig=<ID=chr2,length=242193529>
+##contig=<ID=chr20,length=64444167>
+##contig=<ID=chr21,length=46709983>
+##contig=<ID=chr22,length=50818468>
+##contig=<ID=chr22_KI270731v1_random,length=150754>
+##contig=<ID=chr22_KI270732v1_random,length=41543>
+##contig=<ID=chr22_KI270733v1_random,length=179772>
+##contig=<ID=chr22_KI270734v1_random,length=165050>
+##contig=<ID=chr22_KI270735v1_random,length=42811>
+##contig=<ID=chr22_KI270736v1_random,length=181920>
+##contig=<ID=chr22_KI270737v1_random,length=103838>
+##contig=<ID=chr22_KI270738v1_random,length=99375>
+##contig=<ID=chr22_KI270739v1_random,length=73985>
+##contig=<ID=chr2_KI270715v1_random,length=161471>
+##contig=<ID=chr2_KI270716v1_random,length=153799>
+##contig=<ID=chr3,length=198295559>
+##contig=<ID=chr3_GL000221v1_random,length=155397>
+##contig=<ID=chr4,length=190214555>
+##contig=<ID=chr4_GL000008v2_random,length=209709>
+##contig=<ID=chr5,length=181538259>
+##contig=<ID=chr5_GL000208v1_random,length=92689>
+##contig=<ID=chr6,length=170805979>
+##contig=<ID=chr7,length=159345973>
+##contig=<ID=chr8,length=145138636>
+##contig=<ID=chr9,length=138394717>
+##contig=<ID=chr9_KI270717v1_random,length=40062>
+##contig=<ID=chr9_KI270718v1_random,length=38054>
+##contig=<ID=chr9_KI270719v1_random,length=176845>
+##contig=<ID=chr9_KI270720v1_random,length=39050>
+##contig=<ID=chr1_KI270762v1_alt,length=354444>
+##contig=<ID=chr1_KI270766v1_alt,length=256271>
+##contig=<ID=chr1_KI270760v1_alt,length=109528>
+##contig=<ID=chr1_KI270765v1_alt,length=185285>
+##contig=<ID=chr1_GL383518v1_alt,length=182439>
+##contig=<ID=chr1_GL383519v1_alt,length=110268>
+##contig=<ID=chr1_GL383520v2_alt,length=366580>
+##contig=<ID=chr1_KI270764v1_alt,length=50258>
+##contig=<ID=chr1_KI270763v1_alt,length=911658>
+##contig=<ID=chr1_KI270759v1_alt,length=425601>
+##contig=<ID=chr1_KI270761v1_alt,length=165834>
+##contig=<ID=chr2_KI270770v1_alt,length=136240>
+##contig=<ID=chr2_KI270773v1_alt,length=70887>
+##contig=<ID=chr2_KI270774v1_alt,length=223625>
+##contig=<ID=chr2_KI270769v1_alt,length=120616>
+##contig=<ID=chr2_GL383521v1_alt,length=143390>
+##contig=<ID=chr2_KI270772v1_alt,length=133041>
+##contig=<ID=chr2_KI270775v1_alt,length=138019>
+##contig=<ID=chr2_KI270771v1_alt,length=110395>
+##contig=<ID=chr2_KI270768v1_alt,length=110099>
+##contig=<ID=chr2_GL582966v2_alt,length=96131>
+##contig=<ID=chr2_GL383522v1_alt,length=123821>
+##contig=<ID=chr2_KI270776v1_alt,length=174166>
+##contig=<ID=chr2_KI270767v1_alt,length=161578>
+##contig=<ID=chr3_JH636055v2_alt,length=173151>
+##contig=<ID=chr3_KI270783v1_alt,length=109187>
+##contig=<ID=chr3_KI270780v1_alt,length=224108>
+##contig=<ID=chr3_GL383526v1_alt,length=180671>
+##contig=<ID=chr3_KI270777v1_alt,length=173649>
+##contig=<ID=chr3_KI270778v1_alt,length=248252>
+##contig=<ID=chr3_KI270781v1_alt,length=113034>
+##contig=<ID=chr3_KI270779v1_alt,length=205312>
+##contig=<ID=chr3_KI270782v1_alt,length=162429>
+##contig=<ID=chr3_KI270784v1_alt,length=184404>
+##contig=<ID=chr4_KI270790v1_alt,length=220246>
+##contig=<ID=chr4_GL383528v1_alt,length=376187>
+##contig=<ID=chr4_KI270787v1_alt,length=111943>
+##contig=<ID=chr4_GL000257v2_alt,length=586476>
+##contig=<ID=chr4_KI270788v1_alt,length=158965>
+##contig=<ID=chr4_GL383527v1_alt,length=164536>
+##contig=<ID=chr4_KI270785v1_alt,length=119912>
+##contig=<ID=chr4_KI270789v1_alt,length=205944>
+##contig=<ID=chr4_KI270786v1_alt,length=244096>
+##contig=<ID=chr5_KI270793v1_alt,length=126136>
+##contig=<ID=chr5_KI270792v1_alt,length=179043>
+##contig=<ID=chr5_KI270791v1_alt,length=195710>
+##contig=<ID=chr5_GL383532v1_alt,length=82728>
+##contig=<ID=chr5_GL949742v1_alt,length=226852>
+##contig=<ID=chr5_KI270794v1_alt,length=164558>
+##contig=<ID=chr5_GL339449v2_alt,length=1612928>
+##contig=<ID=chr5_GL383530v1_alt,length=101241>
+##contig=<ID=chr5_KI270796v1_alt,length=172708>
+##contig=<ID=chr5_GL383531v1_alt,length=173459>
+##contig=<ID=chr5_KI270795v1_alt,length=131892>
+##contig=<ID=chr6_GL000250v2_alt,length=4672374>
+##contig=<ID=chr6_KI270800v1_alt,length=175808>
+##contig=<ID=chr6_KI270799v1_alt,length=152148>
+##contig=<ID=chr6_GL383533v1_alt,length=124736>
+##contig=<ID=chr6_KI270801v1_alt,length=870480>
+##contig=<ID=chr6_KI270802v1_alt,length=75005>
+##contig=<ID=chr6_KB021644v2_alt,length=185823>
+##contig=<ID=chr6_KI270797v1_alt,length=197536>
+##contig=<ID=chr6_KI270798v1_alt,length=271782>
+##contig=<ID=chr7_KI270804v1_alt,length=157952>
+##contig=<ID=chr7_KI270809v1_alt,length=209586>
+##contig=<ID=chr7_KI270806v1_alt,length=158166>
+##contig=<ID=chr7_GL383534v2_alt,length=119183>
+##contig=<ID=chr7_KI270803v1_alt,length=1111570>
+##contig=<ID=chr7_KI270808v1_alt,length=271455>
+##contig=<ID=chr7_KI270807v1_alt,length=126434>
+##contig=<ID=chr7_KI270805v1_alt,length=209988>
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+##contig=<ID=chrUn_KI270754v1,length=40191>
+##contig=<ID=chrUn_KI270755v1,length=36723>
+##contig=<ID=chrUn_KI270756v1,length=79590>
+##contig=<ID=chrUn_KI270757v1,length=71251>
+##contig=<ID=chrUn_GL000214v1,length=137718>
+##contig=<ID=chrUn_KI270742v1,length=186739>
+##contig=<ID=chrUn_GL000216v2,length=176608>
+##contig=<ID=chrUn_GL000218v1,length=161147>
+##contig=<ID=chrX,length=156040895>
+##contig=<ID=chrY,length=57227415>
+##contig=<ID=chrY_KI270740v1_random,length=37240>
+##phasing=none
+##commandline= "freebayes  --region  chrY_KI270740v1_random:0..37240  --bam  b_0.bam  --fasta-reference  /panfs/roc/rissdb/galaxy/genomes/hg38/seq/hg38.fa  --vcf  ./vcf_output/part_chrY_KI270740v1_random:0..37240.vcf "
+##INFO=<ID=NS,Number=1,Type=Integer,Description= "Number  of  samples  with  data ">
+##INFO=<ID=DP,Number=1,Type=Integer,Description= "Total  read  depth  at  the  locus ">
+##INFO=<ID=DPB,Number=1,Type=Float,Description= "Total  read  depth  per  bp  at  the  locus;  bases  in  reads  overlapping  /  bases  in  haplotype ">
+##INFO=<ID=AC,Number=A,Type=Integer,Description= "Total  number  of  alternate  alleles  in  called  genotypes ">
+##INFO=<ID=AN,Number=1,Type=Integer,Description= "Total  number  of  alleles  in  called  genotypes ">
+##INFO=<ID=AF,Number=A,Type=Float,Description= "Estimated  allele  frequency  in  the  range  (0,1] ">
+##INFO=<ID=RO,Number=1,Type=Integer,Description= "Count  of  full  observations  of  the  reference  haplotype. ">
+##INFO=<ID=AO,Number=A,Type=Integer,Description= "Count  of  full  observations  of  this  alternate  haplotype. ">
+##INFO=<ID=PRO,Number=1,Type=Float,Description= "Reference  allele  observation  count,  with  partial  observations  recorded  fractionally ">
+##INFO=<ID=PAO,Number=A,Type=Float,Description= "Alternate  allele  observations,  with  partial  observations  recorded  fractionally ">
+##INFO=<ID=QR,Number=1,Type=Integer,Description= "Reference  allele  quality  sum  in  phred ">
+##INFO=<ID=QA,Number=A,Type=Integer,Description= "Alternate  allele  quality  sum  in  phred ">
+##INFO=<ID=PQR,Number=1,Type=Float,Description= "Reference  allele  quality  sum  in  phred  for  partial  observations ">
+##INFO=<ID=PQA,Number=A,Type=Float,Description= "Alternate  allele  quality  sum  in  phred  for  partial  observations ">
+##INFO=<ID=SRF,Number=1,Type=Integer,Description= "Number  of  reference  observations  on  the  forward  strand ">
+##INFO=<ID=SRR,Number=1,Type=Integer,Description= "Number  of  reference  observations  on  the  reverse  strand ">
+##INFO=<ID=SAF,Number=A,Type=Integer,Description= "Number  of  alternate  observations  on  the  forward  strand ">
+##INFO=<ID=SAR,Number=A,Type=Integer,Description= "Number  of  alternate  observations  on  the  reverse  strand ">
+##INFO=<ID=SRP,Number=1,Type=Float,Description= "Strand  balance  probability  for  the  reference  allele:  Phred-scaled  upper-bounds  estimate  of  the  probability  of  observing  the  deviation  between  SRF  and  SRR  given  E(SRF/SRR)  ~  0.5,  derived  using  Hoeffding's  inequality ">
+##INFO=<ID=SAP,Number=A,Type=Float,Description= "Strand  balance  probability  for  the  alternate  allele:  Phred-scaled  upper-bounds  estimate  of  the  probability  of  observing  the  deviation  between  SAF  and  SAR  given  E(SAF/SAR)  ~  0.5,  derived  using  Hoeffding's  inequality ">
+##INFO=<ID=AB,Number=A,Type=Float,Description= "Allele  balance  at  heterozygous  sites:  a  number  between  0  and  1  representing  the  ratio  of  reads  showing  the  reference  allele  to  all  reads,  considering  only  reads  from  individuals  called  as  heterozygous ">
+##INFO=<ID=ABP,Number=A,Type=Float,Description= "Allele  balance  probability  at  heterozygous  sites:  Phred-scaled  upper-bounds  estimate  of  the  probability  of  observing  the  deviation  between  ABR  and  ABA  given  E(ABR/ABA)  ~  0.5,  derived  using  Hoeffding's  inequality ">
+##INFO=<ID=RUN,Number=A,Type=Integer,Description= "Run  length:  the  number  of  consecutive  repeats  of  the  alternate  allele  in  the  reference  genome ">
+##INFO=<ID=RPP,Number=A,Type=Float,Description= "Read  Placement  Probability:  Phred-scaled  upper-bounds  estimate  of  the  probability  of  observing  the  deviation  between  RPL  and  RPR  given  E(RPL/RPR)  ~  0.5,  derived  using  Hoeffding's  inequality ">
+##INFO=<ID=RPPR,Number=1,Type=Float,Description= "Read  Placement  Probability  for  reference  observations:  Phred-scaled  upper-bounds  estimate  of  the  probability  of  observing  the  deviation  between  RPL  and  RPR  given  E(RPL/RPR)  ~  0.5,  derived  using  Hoeffding's  inequality ">
+##INFO=<ID=RPL,Number=A,Type=Float,Description= "Reads  Placed  Left:  number  of  reads  supporting  the  alternate  balanced  to  the  left  (5')  of  the  alternate  allele ">
+##INFO=<ID=RPR,Number=A,Type=Float,Description= "Reads  Placed  Right:  number  of  reads  supporting  the  alternate  balanced  to  the  right  (3')  of  the  alternate  allele ">
+##INFO=<ID=EPP,Number=A,Type=Float,Description= "End  Placement  Probability:  Phred-scaled  upper-bounds  estimate  of  the  probability  of  observing  the  deviation  between  EL  and  ER  given  E(EL/ER)  ~  0.5,  derived  using  Hoeffding's  inequality ">
+##INFO=<ID=EPPR,Number=1,Type=Float,Description= "End  Placement  Probability  for  reference  observations:  Phred-scaled  upper-bounds  estimate  of  the  probability  of  observing  the  deviation  between  EL  and  ER  given  E(EL/ER)  ~  0.5,  derived  using  Hoeffding's  inequality ">
+##INFO=<ID=DPRA,Number=A,Type=Float,Description= "Alternate  allele  depth  ratio.    Ratio  between  depth  in  samples  with  each  called  alternate  allele  and  those  without. ">
+##INFO=<ID=ODDS,Number=1,Type=Float,Description= "The  log  odds  ratio  of  the  best  genotype  combination  to  the  second-best. ">
+##INFO=<ID=GTI,Number=1,Type=Integer,Description= "Number  of  genotyping  iterations  required  to  reach  convergence  or  bailout. ">
+##INFO=<ID=TYPE,Number=A,Type=String,Description= "The  type  of  allele,  either  snp,  mnp,  ins,  del,  or  complex. ">
+##INFO=<ID=CIGAR,Number=A,Type=String,Description= "The  extended  CIGAR  representation  of  each  alternate  allele,  with  the  exception  that  '='  is  replaced  by  'M'  to  ease  VCF  parsing.    Note  that  INDEL  alleles  do  not  have  the  first  matched  base  (which  is  provided  by  default,  per  the  spec)  referred  to  by  the  CIGAR. ">
+##INFO=<ID=NUMALT,Number=1,Type=Integer,Description= "Number  of  unique  non-reference  alleles  in  called  genotypes  at  this  position. ">
+##INFO=<ID=MEANALT,Number=A,Type=Float,Description= "Mean  number  of  unique  non-reference  allele  observations  per  sample  with  the  corresponding  alternate  alleles. ">
+##INFO=<ID=LEN,Number=A,Type=Integer,Description= "allele  length ">
+##INFO=<ID=MQM,Number=A,Type=Float,Description= "Mean  mapping  quality  of  observed  alternate  alleles ">
+##INFO=<ID=MQMR,Number=1,Type=Float,Description= "Mean  mapping  quality  of  observed  reference  alleles ">
+##INFO=<ID=PAIRED,Number=A,Type=Float,Description= "Proportion  of  observed  alternate  alleles  which  are  supported  by  properly  paired  read  fragments ">
+##INFO=<ID=PAIREDR,Number=1,Type=Float,Description= "Proportion  of  observed  reference  alleles  which  are  supported  by  properly  paired  read  fragments ">
+##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description= "Minimum  depth  in  gVCF  output  block. ">
+##INFO=<ID=END,Number=1,Type=Integer,Description= "Last  position  (inclusive)  in  gVCF  output  record. ">
+##FORMAT=<ID=GT,Number=1,Type=String,Description= "Genotype ">
+##FORMAT=<ID=GQ,Number=1,Type=Float,Description= "Genotype  Quality,  the  Phred-scaled  marginal  (or  unconditional)  probability  of  the  called  genotype ">
+##FORMAT=<ID=GL,Number=G,Type=Float,Description= "Genotype  Likelihood,  log10-scaled  likelihoods  of  the  data  given  the  called  genotype  for  each  possible  genotype  generated  from  the  reference  and  alternate  alleles  given  the  sample  ploidy ">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description= "Read  Depth ">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description= "Number  of  observation  for  each  allele ">
+##FORMAT=<ID=RO,Number=1,Type=Integer,Description= "Reference  allele  observation  count ">
+##FORMAT=<ID=QR,Number=1,Type=Integer,Description= "Sum  of  quality  of  the  reference  observations ">
+##FORMAT=<ID=AO,Number=A,Type=Integer,Description= "Alternate  allele  observation  count ">
+##FORMAT=<ID=QA,Number=A,Type=Integer,Description= "Sum  of  quality  of  the  alternate  observations ">
+##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description= "Minimum  depth  in  gVCF  output  block. ">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	unknown
+chr19	18856059	.	C	T	10269.5	.	AB=0.248844;ABP=1306.46;AC=1;AF=0.5;AN=2;AO=592;CIGAR=1X;DP=2379;DPB=2379;DPRA=0;EPP=30.139;EPPR=172.262;GTI=0;LEN=1;MEANALT=2;MQM=60;MQMR=59.9339;NS=1;NUMALT=1;ODDS=2364.65;PAIRED=0.991554;PAIREDR=0.983754;PAO=0;PQA=0;PQR=0;PRO=0;QA=21546;QR=64865;RO=1785;RPL=120;RPP=457.494;RPPR=1043.89;RPR=472;RUN=1;SAF=303;SAP=3.72923;SAR=289;SRF=873;SRP=4.86061;SRR=912;TYPE=snp	GT:DP:AD:RO:QR:AO:QA:GL	0/1:2379:1785,592:1785:64865:592:21546:-1222.54,0,-5112.92
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/variant.tsv	Thu Aug 16 12:27:35 2018 -0400
@@ -0,0 +1,13 @@
+#Variant Report
+#2018-08-13 15:36:32.354483
+#CRAVAT version: hybrid
+#Analysis done at http://www.cravat.us.
+#Job Id: rsajulga_20180813_113614
+#Input file: Freebayes_two_variants.vcf
+#This report shows analysis results at variant level.
+#hg38 genomic.
+#Breast
+#For more information on CRAVAT, visit http://www.cravat.us.
+Input line	ID	Chromosome	Position	Strand	Reference base(s)	Alternate base(s)	Sample ID	HUGO symbol	Sequence ontology	Protein sequence change	Reference peptide	Variant peptide	CHASM p-value	CHASM FDR	ClinVar	COSMIC ID	COSMIC variant count (tissue)	Number of samples with variant	dbSNP	ESP6500 AF (average)	gnomAD AF Total	gnomAD AF African	gnomAD AF American	gnomAD AF Ashkenazi Jewish	gnomAD AF East Asian	gnomAD AF Finnish	gnomAD AF Non-Finnish European	gnomAD AF Other	gnomAD AF South Asian	GWAS NHLBI Key (GRASP)	GWAS PMID (GRASP)	GWAS Phenotype (GRASP)	Protein 3D variant	In TCGA Mutation Cluster	ncRNA Class	ncRNA Name	Pseudogene	Pseudogene Transcript	Repeat Class	Repeat Family	Repeat Name	TARGET	1000 Genomes AF	UTR/Intron	UTR/Intron Gene	UTR/Intron All Transcript	Phred	VCF filters	Zygosity	Alternate reads	Total reads	Variant allele frequency	CGL driver class	S.O. transcript	S.O. transcript strand	S.O. all transcripts	CGC driver class	CGC inheritance	CGC tumor types somatic	CGC tumor types germline	CHASM transcript	CHASM score	All transcripts CHASM results	ClinVar disease identifier	ClinVar XRef	COSMIC transcript	COSMIC protein change	COSMIC variant count	ESP6500 AF (European American)	ESP6500 AF (African American)	HGVS Genomic	HGVS Protein	HGVS Protein All	NCI pathway hits	NCI pathway IDs	NCI pathway names
+1	VAR516_unknown	chr1	156701052	+	C	T	unknown	CRABP2	MS	G24E			0.4176					1		0.0	4.07800406169e-06		2.98044825942e-05										../MuPIT_Interactive?gm=chr1:156701052										0				122.853	.	het	8	20	0.4		ENST00000368221.1	-	*ENST00000368221.1:G24E(MS),ENST00000621784.4:G24E(MS),ENST00000368222.7:G24E(MS)					ENST00000368221.1	0.358	*ENST00000368221.1:G24E(0.358:0.4176),ENST00000368222.7:G24E(0.358:0.4176),ENST00000621784.4:G24E(0.358:0.4176)						0	0	NC_000001.10:g.156701052C>T	ENST00000368221.1:p.Gly24Glu	*ENST00000368221.1:p.Gly24Glu,ENST00000621784.4:p.Gly24Glu,ENST00000368222.7:p.Gly24Glu	0		
+2	VAR517_unknown	chr19	18856059	+	C	T	unknown	UPF1	MS	A571V	EAIDSPVSFLALHNQIR	EAIDSPVSFLVLHNQIR	0.0394			COSM3100527	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr19:18856059										0				10269.5	.	het	592	2379	0.248844052123		ENST00000599848.5	+	ENST00000262803.9:A560V(MS),*ENST00000599848.5:A571V(MS)					ENST00000262803.9	0.63	*ENST00000599848.5:A571V(0.61:0.0530),ENST00000262803.9:A560V(0.63:0.0394)			ENST00000262803	p.A560V (large_intestine 1)	1	0	0	NC_000019.10:g.18856059C>T	ENST00000599848.5:p.Ala571Val	ENST00000262803.9:p.Ala560Val,*ENST00000599848.5:p.Ala571Val	0		
--- a/test-results/Additional_Details.tsv	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,21 +0,0 @@
-#Variant Additional Details Report
-#2018-05-18 15:15:25.120629
-#CRAVAT version: hybrid
-#Analysis done at http://www.cravat.us.
-#Job Id: znylund_20180518_111521
-#Input file: _VCF_BEDintersect_on_data_65_and_data_6_.vcf
-#This report shows analysis results at variant level.
-#hg38 genomic.
-#N/A
-#For more information on CRAVAT, visit http://www.cravat.us.
-
-Input line	ID	Chromosome	Position	Strand	Reference base(s)	Alternate base(s)	Sample ID	HUGO symbol	Sequence ontology	S.O. transcript	S.O. transcript strand	Protein sequence change	S.O. all transcripts	CGC driver class	CGC inheritance	CGC tumor types somatic	CGC tumor types germline	ClinVar disease identifier	ClinVar XRef	COSMIC transcript	COSMIC protein change	COSMIC variant count	ESP6500 AF (European American)	ESP6500 AF (African American)	HGVS Genomic	HGVS Protein	HGVS Protein All	NCI pathway hits	NCI pathway IDs	NCI pathway names	VEST score transcript	VEST p-value	VEST score (missense)	VEST score (frameshift indels)	VEST score (inframe indels)	VEST score (stop-gain)	VEST score (stop-loss)	VEST score (splice site)	All transcripts VEST results
-1	VAR516_unknown	chr1	156705422	+	T	C	unknown	CRABP2	MS	ENST00000368221.1	-	K9E	*ENST00000368221.1:K9E(MS),ENST00000621784.4:K9E(MS),ENST00000368222.7:K9E(MS)							ENST00000368221	p.K9E (large_intestine 1)	1	0	0	NC_000001.10:g.156705422T>C	ENST00000368221.1:p.Lys9Glu	*ENST00000368221.1:p.Lys9Glu,ENST00000621784.4:p.Lys9Glu,ENST00000368222.7:p.Lys9Glu	0			ENST00000368221.1:K9E	0.53061	0.2						*ENST00000368221.1:K9E(0.2:0.53061),ENST00000368222.7:K9E(0.187:0.5543),ENST00000621784.4:K9E(0.186:0.55652)
-2	VAR517_unknown	chr12	6561055	+	T	C	unknown	NOP2	MS	ENST00000616948.4	-	N408S	ENST00000617555.4:N404S(MS),ENST00000545200.5:N404S(MS),ENST00000541778.5:N404S(MS),ENST00000399466.6:N404S(MS),ENST00000322166.9:N408S(MS),ENST00000537442.5:N408S(MS),ENST00000382421.7:N441S(MS),ENST00000620535.4:N441S(MS),*ENST00000616948.4:N408S(MS)										0	0	NC_000012.10:g.6561055T>C	ENST00000616948.4:p.Asn408Ser	ENST00000617555.4:p.Asn404Ser,ENST00000545200.5:p.Asn404Ser,ENST00000541778.5:p.Asn404Ser,ENST00000399466.6:p.Asn404Ser,ENST00000322166.9:p.Asn408Ser,ENST00000537442.5:p.Asn408Ser,ENST00000382421.7:p.Asn441Ser,ENST00000620535.4:p.Asn441Ser,*ENST00000616948.4:p.Asn408Ser	0			ENST00000616948.4:N408S	0.00324	0.958						ENST00000617555.4:N404S(0.954:0.00354),*ENST00000616948.4:N408S(0.958:0.00324),ENST00000541778.5:N404S(0.869:0.01488),ENST00000537442.5:N408S(0.956:0.00344),ENST00000399466.6:N404S(0.951:0.00374),ENST00000545200.5:N404S(0.953:0.00354),ENST00000620535.4:N441S(0.938:0.00536),ENST00000382421.7:N441S(0.938:0.00536),ENST00000322166.9:N408S(0.954:0.00354)
-3	VAR518_unknown	chr12	110339630	+	C	T	unknown	ATP2A2	MS	ENST00000539276.6	+	T557I	ENST00000308664.10:T557I(MS),*ENST00000539276.6:T557I(MS)										0	0	NC_000012.10:g.110339630C>T	ENST00000539276.6:p.Thr557Ile	ENST00000308664.10:p.Thr557Ile,*ENST00000539276.6:p.Thr557Ile	0			ENST00000539276.6:T557I	0.00374	0.951						ENST00000308664.10:T557I(0.822:0.02459),*ENST00000539276.6:T557I(0.951:0.00374)
-4	VAR520_unknown	chr14	102011985	+	A	T	unknown	DYNC1H1	MS	ENST00000360184.8	+	R2243S	*ENST00000360184.8:R2243S(MS)							ENST00000360184	p.R2243S (large_intestine 1)	1	0	0	NC_000014.10:g.102011985A>T	ENST00000360184.8:p.Arg2243Ser	*ENST00000360184.8:p.Arg2243Ser	1	94da5dd8-5521-11e7-8f50-0ac135e8bacf	Lissencephaly gene (LIS1) in neuronal migration and development	ENST00000360184.8:R2243S	0.02307	0.829						*ENST00000360184.8:R2243S(0.829:0.02307)
-5	VAR521_unknown	chr14	102083954	+	C	T	unknown	HSP90AA1	MS	ENST00000334701.11	-	D515N	ENST00000216281.12:D393N(MS),*ENST00000334701.11:D515N(MS)		somatic	NHL				ENST00000334701	p.D515N (large_intestine 1)	1	0	0	NC_000014.10:g.102083954C>T	ENST00000334701.11:p.Asp515Asn	ENST00000216281.12:p.Asp393Asn,*ENST00000334701.11:p.Asp515Asn	15	3814fa62-5521-11e7-8f50-0ac135e8bacf,32ff1916-5521-11e7-8f50-0ac135e8bacf,a8411a5c-5521-11e7-8f50-0ac135e8bacf,541d7e20-5521-11e7-8f50-0ac135e8bacf,98ad85f0-5521-11e7-8f50-0ac135e8bacf,9697501e-5521-11e7-8f50-0ac135e8bacf,e6f69242-5521-11e7-8f50-0ac135e8bacf,603902ca-5521-11e7-8f50-0ac135e8bacf,bb3d7c4a-5521-11e7-8f50-0ac135e8bacf,b1ac7318-5521-11e7-8f50-0ac135e8bacf,cb348d72-5521-11e7-8f50-0ac135e8bacf,945aa686-5521-11e7-8f50-0ac135e8bacf,4c90f780-5521-11e7-8f50-0ac135e8bacf,e4e93610-5521-11e7-8f50-0ac135e8bacf,6f7a316e-5521-11e7-8f50-0ac135e8bacf	Validated targets of C-MYC transcriptional activation@VEGFR1 specific signals@IL2 signaling events mediated by PI3K@Signaling events mediated by HDAC Class II@Integrin-linked kinase signaling@Integrins in angiogenesis@Class I PI3K signaling events mediated by Akt@Regulation of Telomerase@Glucocorticoid receptor regulatory network@Hypoxic and oxygen homeostasis regulation of HIF-1-alpha@ErbB receptor signaling network@LKB1 signaling events@Signaling events mediated by VEGFR1 and VEGFR2@Class I PI3K signaling events@Regulation of Androgen receptor activity	ENST00000216281.12:D393N	0.02014	0.84						ENST00000334701.11:D515N(0.749:0.04989),*ENST00000216281.12:D393N(0.84:0.02014)
-6	VAR522_unknown	chr17	82082606	+	C	T	unknown	FASN	MS	ENST00000306749.3	-	S1947N	ENST00000634990.1:S1945N(MS),*ENST00000306749.3:S1947N(MS)							ENST00000306749	p.S1947N (large_intestine 1)	1	0	0	NC_000017.10:g.82082606C>T	ENST00000306749.3:p.Ser1947Asn	ENST00000634990.1:p.Ser1945Asn,*ENST00000306749.3:p.Ser1947Asn	2	34a994cc-5521-11e7-8f50-0ac135e8bacf,812903c2-5521-11e7-8f50-0ac135e8bacf	Validated transcriptional targets of deltaNp63 isoforms@p73 transcription factor network	ENST00000634990.1:S1945N	0.18611	0.501						ENST00000306749.3:S1947N(0.493:0.19016),*ENST00000634990.1:S1945N(0.501:0.18611)
-7	VAR523_unknown	chr19	17205335	+	A	T	unknown	MYO9B	MS	ENST00000594824.5	+	K1688M	ENST00000397274.6:K1688M(MS),ENST00000595618.5:K1688M(MS),*ENST00000594824.5:K1688M(MS)										0	0	NC_000019.10:g.17205335A>T	ENST00000594824.5:p.Lys1688Met	ENST00000397274.6:p.Lys1688Met,ENST00000595618.5:p.Lys1688Met,*ENST00000594824.5:p.Lys1688Met	1	60f3521c-5521-11e7-8f50-0ac135e8bacf	Regulation of RhoA activity	ENST00000397274.6:K1688M	0.20028	0.473						ENST00000594824.5:K1688M(0.464:0.20464),*ENST00000397274.6:K1688M(0.473:0.20028),ENST00000595618.5:K1688M(0.469:0.20231)
-9	VAR525_unknown	chr19	17205973	+	T	C	unknown	MYO9B	MS	ENST00000594824.5	+	V1693A	ENST00000397274.6:V1693A(MS),ENST00000595618.5:V1693A(MS),*ENST00000594824.5:V1693A(MS)							ENST00000319396	p.V1693A (thyroid 2)	2	0.399857	0.645631	NC_000019.10:g.17205973T>C	ENST00000594824.5:p.Val1693Ala	ENST00000397274.6:p.Val1693Ala,ENST00000595618.5:p.Val1693Ala,*ENST00000594824.5:p.Val1693Ala	1	60f3521c-5521-11e7-8f50-0ac135e8bacf	Regulation of RhoA activity	ENST00000397274.6:V1693A	0.95254	0.045						ENST00000594824.5:V1693A(0.025:0.98158),*ENST00000397274.6:V1693A(0.045:0.95254),ENST00000595618.5:V1693A(0.042:0.95749)
-10	VAR526_unknown	chr19	18856059	+	C	T	unknown	UPF1	MS	ENST00000599848.5	+	A571V	ENST00000262803.9:A560V(MS),*ENST00000599848.5:A571V(MS)							ENST00000262803	p.A560V (large_intestine 1)	1	0	0	NC_000019.10:g.18856059C>T	ENST00000599848.5:p.Ala571Val	ENST00000262803.9:p.Ala560Val,*ENST00000599848.5:p.Ala571Val	0			ENST00000262803.9:A560V	0.09372	0.662						ENST00000599848.5:A571V(0.643:0.10292),*ENST00000262803.9:A560V(0.662:0.09372)
--- a/test-results/Gene_Level_Analysis.tsv	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,21 +0,0 @@
-#Gene Level Annotation Report
-#2018-05-18 15:18:04.023450
-#CRAVAT version: hybrid
-#Analysis done at http://www.cravat.us.
-#Job Id: znylund_20180518_111800
-#Input file: _VCF_BEDintersect_on_data_65_and_data_6_.vcf
-#This report shows analysis results at gene level.
-#The composite p-value (Stouffer's combined p-value) and composite FDR of a gene show how probable it is to get the same p-value distribution for the gene as that obtained from the input variants by chance.
-#hg38 genomic.
-#N/A
-#For more information on CRAVAT, visit http://www.cravat.us.
-
-HUGO symbol	Number of variants	Sequence ontology	CGC driver class	CGC inheritance	CGC tumor types somatic	CGC tumor types germline	ClinVar disease identifier	ClinVar XRef	Occurrences in COSMIC	COSMIC gene count (tissue)	Number of samples with gene mutated	CHASM gene score	CHASM gene p-value	CHASM gene FDR	VEST gene score (non-silent)	VEST gene p-value	VEST gene FDR	Protein 3D gene	Has a mutation in a TCGA Mutation Cluster	NCI pathway hits	NCI pathway IDs	NCI pathway names	TARGET	CGL driver class
-CRABP2	1	MS							37	upper_aerodigestive_tract(3);large_intestine(9);stomach(4);soft_tissue(3);endometrium(4);lung(3);liver(2);skin(4);NS(1);prostate(1);bone(1);kidney(1);breast(1)	1				0.2	0.53061	0.65	../MuPIT_Interactive?gm=chr1:156705422		0				
-NOP2	1	MS							133	large_intestine(22);endometrium(8);lung(8);skin(20);kidney(5);thyroid(1);cervix(2);central_nervous_system(3);oesophagus(4);NS(2);upper_aerodigestive_tract(5);stomach(8);soft_tissue(1);urinary_tract(4);breast(12);prostate(5);pituitary(1);pancreas(5);adrenal_gland(1);haematopoietic_and_lymphoid_tissue(2);ovary(5);liver(9)	1				0.958	0.00324	0.05	../MuPIT_Interactive?gm=chr12:6561055		0				
-ATP2A2	1	MS					C0022595	OMIM:124200	200	large_intestine(31);endometrium(12);lung(7);skin(43);autonomic_ganglia(1);kidney(9);thyroid(3);cervix(2);testis(1);oesophagus(4);NS(2);upper_aerodigestive_tract(6);biliary_tract(6);stomach(14);soft_tissue(2);urinary_tract(8);breast(7);prostate(8);pancreas(6);small_intestine(2);haematopoietic_and_lymphoid_tissue(5);ovary(3);bone(2);liver(16)	1				0.951	0.00374	0.05	../MuPIT_Interactive?gm=chr12:110339630		0				
-DYNC1H1	1	MS					C1834690	OMIM:158600	955	large_intestine(151);pleura(1);endometrium(79);lung(62);skin(151);autonomic_ganglia(1);kidney(27);thyroid(8);cervix(13);testis(1);central_nervous_system(12);oesophagus(28);NS(19);upper_aerodigestive_tract(31);biliary_tract(6);stomach(60);soft_tissue(13);urinary_tract(25);breast(50);prostate(38);pancreas(18);adrenal_gland(3);meninges(1);small_intestine(3);haematopoietic_and_lymphoid_tissue(37);ovary(20);bone(4);liver(93)	1				0.829	0.02307	0.1	../MuPIT_Interactive?gm=chr14:102011985		1	94da5dd8-5521-11e7-8f50-0ac135e8bacf	Lissencephaly gene (LIS1) in neuronal migration and development		
-HSP90AA1	1	MS		somatic	NHL				174	large_intestine(19);endometrium(9);lung(9);skin(25);kidney(12);thyroid(2);cervix(4);central_nervous_system(2);oesophagus(9);NS(5);biliary_tract(2);stomach(16);soft_tissue(5);urinary_tract(15);liver(11);prostate(3);pancreas(1);salivary_gland(1);haematopoietic_and_lymphoid_tissue(5);ovary(8);bone(1);breast(10)	1				0.84	0.02014	0.1	../MuPIT_Interactive?gm=chr14:102083954		15	3814fa62-5521-11e7-8f50-0ac135e8bacf,32ff1916-5521-11e7-8f50-0ac135e8bacf,a8411a5c-5521-11e7-8f50-0ac135e8bacf,541d7e20-5521-11e7-8f50-0ac135e8bacf,98ad85f0-5521-11e7-8f50-0ac135e8bacf,9697501e-5521-11e7-8f50-0ac135e8bacf,e6f69242-5521-11e7-8f50-0ac135e8bacf,603902ca-5521-11e7-8f50-0ac135e8bacf,bb3d7c4a-5521-11e7-8f50-0ac135e8bacf,b1ac7318-5521-11e7-8f50-0ac135e8bacf,cb348d72-5521-11e7-8f50-0ac135e8bacf,945aa686-5521-11e7-8f50-0ac135e8bacf,4c90f780-5521-11e7-8f50-0ac135e8bacf,e4e93610-5521-11e7-8f50-0ac135e8bacf,6f7a316e-5521-11e7-8f50-0ac135e8bacf	Validated targets of C-MYC transcriptional activation@VEGFR1 specific signals@IL2 signaling events mediated by PI3K@Signaling events mediated by HDAC Class II@Integrin-linked kinase signaling@Integrins in angiogenesis@Class I PI3K signaling events mediated by Akt@Regulation of Telomerase@Glucocorticoid receptor regulatory network@Hypoxic and oxygen homeostasis regulation of HIF-1-alpha@ErbB receptor signaling network@LKB1 signaling events@Signaling events mediated by VEGFR1 and VEGFR2@Class I PI3K signaling events@Regulation of Androgen receptor activity		
-FASN	1	MS							621	large_intestine(163);endometrium(22);lung(19);skin(82);autonomic_ganglia(1);kidney(9);thyroid(7);cervix(9);central_nervous_system(7);genital_tract(1);oesophagus(24);NS(13);upper_aerodigestive_tract(21);biliary_tract(12);stomach(39);soft_tissue(9);urinary_tract(2);liver(79);prostate(20);pancreas(14);adrenal_gland(2);salivary_gland(3);small_intestine(4);haematopoietic_and_lymphoid_tissue(14);ovary(3);bone(5);breast(37)	1				0.501	0.18611	0.25	../MuPIT_Interactive?gm=chr17:82082606		2	34a994cc-5521-11e7-8f50-0ac135e8bacf,812903c2-5521-11e7-8f50-0ac135e8bacf	Validated transcriptional targets of deltaNp63 isoforms@p73 transcription factor network		
-MYO9B	2	MS					C1857847	OMIM:609753	424	large_intestine(96);endometrium(33);lung(17);skin(57);kidney(12);thyroid(9);cervix(4);central_nervous_system(9);oesophagus(22);NS(8);upper_aerodigestive_tract(22);biliary_tract(9);stomach(24);soft_tissue(10);urinary_tract(8);breast(17);prostate(14);pancreas(15);adrenal_gland(4);haematopoietic_and_lymphoid_tissue(8);ovary(1);bone(4);liver(21)	1				0.473	0.721215732958585	1	../MuPIT_Interactive?gm=chr19:17205335,chr19:17205973		1	60f3521c-5521-11e7-8f50-0ac135e8bacf	Regulation of RhoA activity		
-UPF1	1	MS							267	large_intestine(57);endometrium(18);lung(13);skin(45);meninges(1);kidney(9);thyroid(3);cervix(4);central_nervous_system(7);oesophagus(5);NS(4);upper_aerodigestive_tract(10);biliary_tract(2);stomach(15);soft_tissue(6);urinary_tract(12);breast(11);prostate(7);pancreas(7);haematopoietic_and_lymphoid_tissue(10);ovary(4);bone(2);liver(15)	1				0.662	0.09372	0.15	../MuPIT_Interactive?gm=chr19:18856059						
--- a/test-results/Input_Errors.Result.tsv	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,12 +0,0 @@
-#Input Errors Report
-#2018-05-18 15:18:04.022947
-#CRAVAT version: hybrid
-#Analysis done at http://www.cravat.us.
-#Job Id: znylund_20180518_111800
-#Input file: _VCF_BEDintersect_on_data_65_and_data_6_.vcf
-#This report shows errors that occurred in the input.
-#Input coordinate: hg38 genomic.
-#CHASM classifier: N/A
-#For more information on CRAVAT, visit http://www.cravat.us.
-
-Input line number$%$Input line UID$%$Gene$%$Error$%$Input Line
--- a/test-results/Variant_Non-coding.Result.tsv	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,13 +0,0 @@
-#Non-coding Variant Report
-#2018-05-18 15:18:04.020642
-#CRAVAT version: hybrid
-#Analysis done at http://www.cravat.us.
-#Job Id: znylund_20180518_111800
-#Input file: _VCF_BEDintersect_on_data_65_and_data_6_.vcf
-#This report shows analysis results at variant level.
-#hg38 genomic.
-#N/A
-#For more information on CRAVAT, visit http://www.cravat.us.
-
-Input line	ID	Chromosome	Position	Strand	Reference base(s)	Alternate base(s)	Sample ID	HUGO symbol	Sequence ontology	Protein sequence change	ClinVar	COSMIC ID	COSMIC variant count (tissue)	Number of samples with variant	dbSNP	ESP6500 AF (average)	gnomAD AF Total	gnomAD AF African	gnomAD AF American	gnomAD AF Ashkenazi Jewish	gnomAD AF East Asian	gnomAD AF Finnish	gnomAD AF Non-Finnish European	gnomAD AF Other	gnomAD AF South Asian	GWAS NHLBI Key (GRASP)	GWAS PMID (GRASP)	GWAS Phenotype (GRASP)	Protein 3D variant	In TCGA Mutation Cluster	ncRNA Class	ncRNA Name	Pseudogene	Pseudogene Transcript	Repeat Class	Repeat Family	Repeat Name	TARGET	1000 Genomes AF	UTR/Intron	UTR/Intron Gene	UTR/Intron All Transcript	Phred	VCF filters	Zygosity	Alternate reads	Total reads	Variant allele frequency	VEST p-value	VEST FDR	CGL driver class
-8	VAR524_unknown	chr19	17205444	+	T	C	unknown	Non-Coding						1	rs2305763	0.0	0.510502431118	0.684095610205	0.693317422434	0.337748344371	0.795930949445	0.435243553009	0.393043827905	0.449691991786															0.629792	intron	MYO9B	ENST00000595618.5(intron),ENST00000594824.5(intron),ENST00000397274.6(intron)	206.198	.	hom	14	7	2.0			
--- a/test-results/Variant_Result.tsv	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,21 +0,0 @@
-#Variant Report
-#2018-05-18 15:15:25.119179
-#CRAVAT version: hybrid
-#Analysis done at http://www.cravat.us.
-#Job Id: znylund_20180518_111521
-#Input file: _VCF_BEDintersect_on_data_65_and_data_6_.vcf
-#This report shows analysis results at variant level.
-#hg38 genomic.
-#N/A
-#For more information on CRAVAT, visit http://www.cravat.us.
-
-Input line	ID	Chromosome	Position	Strand	Reference base(s)	Alternate base(s)	Sample ID	HUGO symbol	Sequence ontology	Protein sequence change	ClinVar	COSMIC ID	COSMIC variant count (tissue)	Number of samples with variant	dbSNP	ESP6500 AF (average)	gnomAD AF Total	gnomAD AF African	gnomAD AF American	gnomAD AF Ashkenazi Jewish	gnomAD AF East Asian	gnomAD AF Finnish	gnomAD AF Non-Finnish European	gnomAD AF Other	gnomAD AF South Asian	GWAS NHLBI Key (GRASP)	GWAS PMID (GRASP)	GWAS Phenotype (GRASP)	Protein 3D variant	In TCGA Mutation Cluster	ncRNA Class	ncRNA Name	Pseudogene	Pseudogene Transcript	Repeat Class	Repeat Family	Repeat Name	TARGET	1000 Genomes AF	UTR/Intron	UTR/Intron Gene	UTR/Intron All Transcript	Phred	VCF filters	Zygosity	Alternate reads	Total reads	Variant allele frequency	VEST p-value	VEST FDR	CGL driver class
-1	VAR516_unknown	chr1	156705422	+	T	C	unknown	CRABP2	MS	K9E		COSM1984142	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr1:156705422										0				125181	.	het	5739	18018	0.318514818515	0.53061		
-2	VAR517_unknown	chr12	6561055	+	T	C	unknown	NOP2	MS	N408S				1		0.0													../MuPIT_Interactive?gm=chr12:6561055										0				14340.8	.	het	910	3868	0.235263702172	0.00324		
-3	VAR518_unknown	chr12	110339630	+	C	T	unknown	ATP2A2	MS	T557I				1		0.0													../MuPIT_Interactive?gm=chr12:110339630										0				48828.1	.	het	2447	9100	0.268901098901	0.00374		
-4	VAR520_unknown	chr14	102011985	+	A	T	unknown	DYNC1H1	MS	R2243S		COSM2262213	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr14:102011985										0				12962.3	.	het	642	2131	0.301267010793	0.02307		
-5	VAR521_unknown	chr14	102083954	+	C	T	unknown	HSP90AA1	MS	D515N		COSM2262393	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr14:102083954										0				240809	.	het	17374	85275	0.203740838464	0.02014		
-6	VAR522_unknown	chr17	82082606	+	C	T	unknown	FASN	MS	S1947N		COSM4648107	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr17:82082606										0				10374.8	.	het	776	3826	0.202822791427	0.18611		
-7	VAR523_unknown	chr19	17205335	+	A	T	unknown	MYO9B	MS	K1688M				1		0.0													../MuPIT_Interactive?gm=chr19:17205335										0				0.00158993	.	het	2	7	0.285714285714	0.20028		
-9	VAR525_unknown	chr19	17205973	+	T	C	unknown	MYO9B	MS	V1693A		COSM438878	thyroid(2)	1	rs7248508	0.522744	0.526958747465	0.685404424473	0.728029336735	0.352247807018	0.776672496721	0.453231381586	0.406255640183	0.486462728551	0.596900776808	190609063506732,203395363506733,206865653506734,208819603506735,224846277709335,224792027709336	19060906,20339536,20686565,20881960,22484627,22479202	LDL cholesterol(0.0152),HDL cholesterol(0.0279),Triglycerides(0.0141),Height(0.0104),Obesity with early age of onset (age >2)(0.0471),Adiponectin levels(0.0294)	../MuPIT_Interactive?gm=chr19:17205973										0.631589				12243.8	.	hom	812	406	2.0	0.95254		
-10	VAR526_unknown	chr19	18856059	+	C	T	unknown	UPF1	MS	A571V		COSM3100527	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr19:18856059										0				10269.5	.	het	592	2379	0.248844052123	0.09372		
--- a/test-results/combined_variants.tsv	Fri May 18 13:25:29 2018 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,21 +0,0 @@
-#Variant Additional Details Report
-#2018-05-18 15:15:25.120629
-#CRAVAT version: hybrid
-#Analysis done at http://www.cravat.us.
-#Job Id: znylund_20180518_111521
-#Input file: _VCF_BEDintersect_on_data_65_and_data_6_.vcf
-#This report shows analysis results at variant level.
-#hg38 genomic.
-#N/A
-#For more information on CRAVAT, visit http://www.cravat.us.
-
-Input line	ID	Chromosome	Position	Strand	Reference base(s)	Alternate base(s)	Sample ID	HUGO symbol	Sequence ontology	S.O. transcript	S.O. transcript strand	Reference peptide	Variant peptide	Protein sequence change	S.O. all transcripts	CGC driver class	CGC inheritance	CGC tumor types somatic	CGC tumor types germline	ClinVar disease identifier	ClinVar XRef	COSMIC transcript	COSMIC protein change	COSMIC variant count	ESP6500 AF (European American)	ESP6500 AF (African American)	HGVS Genomic	HGVS Protein	HGVS Protein All	NCI pathway hits	NCI pathway IDs	NCI pathway names	VEST score transcript	VEST p-value	VEST score (missense)	VEST score (frameshift indels)	VEST score (inframe indels)	VEST score (stop-gain)	VEST score (stop-loss)	VEST score (splice site)	All transcripts VEST results	ClinVar	COSMIC ID	COSMIC variant count (tissue)	Number of samples with variant	dbSNP	ESP6500 AF (average)	gnomAD AF Total	gnomAD AF African	gnomAD AF American	gnomAD AF Ashkenazi Jewish	gnomAD AF East Asian	gnomAD AF Finnish	gnomAD AF Non-Finnish European	gnomAD AF Other	gnomAD AF South Asian	GWAS NHLBI Key (GRASP)	GWAS PMID (GRASP)	GWAS Phenotype (GRASP)	Protein 3D variant	In TCGA Mutation Cluster	ncRNA Class	ncRNA Name	Pseudogene	Pseudogene Transcript	Repeat Class	Repeat Family	Repeat Name	TARGET	1000 Genomes AF	UTR/Intron	UTR/Intron Gene	UTR/Intron All Transcript	Phred	VCF filters	Zygosity	Alternate reads	Total reads	Variant allele frequency	VEST FDR	CGL driver class
-1	VAR516_unknown	chr1	156705422	+	T	C	unknown	CRABP2	MS	ENST00000368221.1	-	MPNFSGNWKIIR	MPNFSGNWEIIR	K9E	*ENST00000368221.1:K9E(MS),ENST00000621784.4:K9E(MS),ENST00000368222.7:K9E(MS)							ENST00000368221	p.K9E (large_intestine 1)	1	0	0	NC_000001.10:g.156705422T>C	ENST00000368221.1:p.Lys9Glu	*ENST00000368221.1:p.Lys9Glu,ENST00000621784.4:p.Lys9Glu,ENST00000368222.7:p.Lys9Glu	0			ENST00000368221.1:K9E	0.53061	0.2						*ENST00000368221.1:K9E(0.2:0.53061),ENST00000368222.7:K9E(0.187:0.5543),ENST00000621784.4:K9E(0.186:0.55652)		COSM1984142	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr1:156705422										0				125181	.	het	5739	18018	0.318514818515		
-2	VAR517_unknown	chr12	6561055	+	T	C	unknown	NOP2	MS	ENST00000616948.4	-	NTGVILANDANAER	STGVILANDANAER	N408S	ENST00000617555.4:N404S(MS),ENST00000545200.5:N404S(MS),ENST00000541778.5:N404S(MS),ENST00000399466.6:N404S(MS),ENST00000322166.9:N408S(MS),ENST00000537442.5:N408S(MS),ENST00000382421.7:N441S(MS),ENST00000620535.4:N441S(MS),*ENST00000616948.4:N408S(MS)										0	0	NC_000012.10:g.6561055T>C	ENST00000616948.4:p.Asn408Ser	ENST00000617555.4:p.Asn404Ser,ENST00000545200.5:p.Asn404Ser,ENST00000541778.5:p.Asn404Ser,ENST00000399466.6:p.Asn404Ser,ENST00000322166.9:p.Asn408Ser,ENST00000537442.5:p.Asn408Ser,ENST00000382421.7:p.Asn441Ser,ENST00000620535.4:p.Asn441Ser,*ENST00000616948.4:p.Asn408Ser	0			ENST00000616948.4:N408S	0.00324	0.958						ENST00000617555.4:N404S(0.954:0.00354),*ENST00000616948.4:N408S(0.958:0.00324),ENST00000541778.5:N404S(0.869:0.01488),ENST00000537442.5:N408S(0.956:0.00344),ENST00000399466.6:N404S(0.951:0.00374),ENST00000545200.5:N404S(0.953:0.00354),ENST00000620535.4:N441S(0.938:0.00536),ENST00000382421.7:N441S(0.938:0.00536),ENST00000322166.9:N408S(0.954:0.00354)				1		0.0													../MuPIT_Interactive?gm=chr12:6561055										0				14340.8	.	het	910	3868	0.235263702172		
-3	VAR518_unknown	chr12	110339630	+	C	T	unknown	ATP2A2	MS	ENST00000539276.6	+	EWGSGSDTLR	EWGSGSDILR	T557I	ENST00000308664.10:T557I(MS),*ENST00000539276.6:T557I(MS)										0	0	NC_000012.10:g.110339630C>T	ENST00000539276.6:p.Thr557Ile	ENST00000308664.10:p.Thr557Ile,*ENST00000539276.6:p.Thr557Ile	0			ENST00000539276.6:T557I	0.00374	0.951						ENST00000308664.10:T557I(0.822:0.02459),*ENST00000539276.6:T557I(0.951:0.00374)				1		0.0													../MuPIT_Interactive?gm=chr12:110339630										0				48828.1	.	het	2447	9100	0.268901098901		
-4	VAR520_unknown	chr14	102011985	+	A	T	unknown	DYNC1H1	MS	ENST00000360184.8	+	ALERLEGVEGVAHIIDPK	ALESLEGVEGVAHIIDPK	R2243S	*ENST00000360184.8:R2243S(MS)							ENST00000360184	p.R2243S (large_intestine 1)	1	0	0	NC_000014.10:g.102011985A>T	ENST00000360184.8:p.Arg2243Ser	*ENST00000360184.8:p.Arg2243Ser	1	94da5dd8-5521-11e7-8f50-0ac135e8bacf	Lissencephaly gene (LIS1) in neuronal migration and development	ENST00000360184.8:R2243S	0.02307	0.829						*ENST00000360184.8:R2243S(0.829:0.02307)		COSM2262213	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr14:102011985										0				12962.3	.	het	642	2131	0.301267010793		
-5	VAR521_unknown	chr14	102083954	+	C	T	unknown	HSP90AA1	MS	ENST00000334701.11	-	GVVDSEDLPLNISR	GVVDSENLPLNISR	D515N	ENST00000216281.12:D393N(MS),*ENST00000334701.11:D515N(MS)		somatic	NHL				ENST00000334701	p.D515N (large_intestine 1)	1	0	0	NC_000014.10:g.102083954C>T	ENST00000334701.11:p.Asp515Asn	ENST00000216281.12:p.Asp393Asn,*ENST00000334701.11:p.Asp515Asn	15	3814fa62-5521-11e7-8f50-0ac135e8bacf,32ff1916-5521-11e7-8f50-0ac135e8bacf,a8411a5c-5521-11e7-8f50-0ac135e8bacf,541d7e20-5521-11e7-8f50-0ac135e8bacf,98ad85f0-5521-11e7-8f50-0ac135e8bacf,9697501e-5521-11e7-8f50-0ac135e8bacf,e6f69242-5521-11e7-8f50-0ac135e8bacf,603902ca-5521-11e7-8f50-0ac135e8bacf,bb3d7c4a-5521-11e7-8f50-0ac135e8bacf,b1ac7318-5521-11e7-8f50-0ac135e8bacf,cb348d72-5521-11e7-8f50-0ac135e8bacf,945aa686-5521-11e7-8f50-0ac135e8bacf,4c90f780-5521-11e7-8f50-0ac135e8bacf,e4e93610-5521-11e7-8f50-0ac135e8bacf,6f7a316e-5521-11e7-8f50-0ac135e8bacf	Validated targets of C-MYC transcriptional activation@VEGFR1 specific signals@IL2 signaling events mediated by PI3K@Signaling events mediated by HDAC Class II@Integrin-linked kinase signaling@Integrins in angiogenesis@Class I PI3K signaling events mediated by Akt@Regulation of Telomerase@Glucocorticoid receptor regulatory network@Hypoxic and oxygen homeostasis regulation of HIF-1-alpha@ErbB receptor signaling network@LKB1 signaling events@Signaling events mediated by VEGFR1 and VEGFR2@Class I PI3K signaling events@Regulation of Androgen receptor activity	ENST00000216281.12:D393N	0.02014	0.84						ENST00000334701.11:D515N(0.749:0.04989),*ENST00000216281.12:D393N(0.84:0.02014)		COSM2262393	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr14:102083954										0				240809	.	het	17374	85275	0.203740838464		
-6	VAR522_unknown	chr17	82082606	+	C	T	unknown	FASN	MS	ENST00000306749.3	-	QGVQVQVSTSNISSLEGAR	QGVQVQVSTSNINSLEGAR	S1947N	ENST00000634990.1:S1945N(MS),*ENST00000306749.3:S1947N(MS)							ENST00000306749	p.S1947N (large_intestine 1)	1	0	0	NC_000017.10:g.82082606C>T	ENST00000306749.3:p.Ser1947Asn	ENST00000634990.1:p.Ser1945Asn,*ENST00000306749.3:p.Ser1947Asn	2	34a994cc-5521-11e7-8f50-0ac135e8bacf,812903c2-5521-11e7-8f50-0ac135e8bacf	Validated transcriptional targets of deltaNp63 isoforms@p73 transcription factor network	ENST00000634990.1:S1945N	0.18611	0.501						ENST00000306749.3:S1947N(0.493:0.19016),*ENST00000634990.1:S1945N(0.501:0.18611)		COSM4648107	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr17:82082606										0				10374.8	.	het	776	3826	0.202822791427		
-7	VAR523_unknown	chr19	17205335	+	A	T	unknown	MYO9B	MS	ENST00000594824.5	+	IQSHCSYTYGRKGEPGVEPGHFGVCVDSLTSDK	IQSHCSYTYGRMGEPGAEPGHFGVCVDSLTSDK	K1688M	ENST00000397274.6:K1688M(MS),ENST00000595618.5:K1688M(MS),*ENST00000594824.5:K1688M(MS)										0	0	NC_000019.10:g.17205335A>T	ENST00000594824.5:p.Lys1688Met	ENST00000397274.6:p.Lys1688Met,ENST00000595618.5:p.Lys1688Met,*ENST00000594824.5:p.Lys1688Met	1	60f3521c-5521-11e7-8f50-0ac135e8bacf	Regulation of RhoA activity	ENST00000397274.6:K1688M	0.20028	0.473						ENST00000594824.5:K1688M(0.464:0.20464),*ENST00000397274.6:K1688M(0.473:0.20028),ENST00000595618.5:K1688M(0.469:0.20231)				1		0.0													../MuPIT_Interactive?gm=chr19:17205335										0				0.00158993	.	het	2	7	0.285714285714		
-9	VAR525_unknown	chr19	17205973	+	T	C	unknown	MYO9B	MS	ENST00000594824.5	+	IQSHCSYTYGRKGEPGVEPGHFGVCVDSLTSDK	IQSHCSYTYGRMGEPGAEPGHFGVCVDSLTSDK	V1693A	ENST00000397274.6:V1693A(MS),ENST00000595618.5:V1693A(MS),*ENST00000594824.5:V1693A(MS)							ENST00000319396	p.V1693A (thyroid 2)	2	0.399857	0.645631	NC_000019.10:g.17205973T>C	ENST00000594824.5:p.Val1693Ala	ENST00000397274.6:p.Val1693Ala,ENST00000595618.5:p.Val1693Ala,*ENST00000594824.5:p.Val1693Ala	1	60f3521c-5521-11e7-8f50-0ac135e8bacf	Regulation of RhoA activity	ENST00000397274.6:V1693A	0.95254	0.045						ENST00000594824.5:V1693A(0.025:0.98158),*ENST00000397274.6:V1693A(0.045:0.95254),ENST00000595618.5:V1693A(0.042:0.95749)		COSM438878	thyroid(2)	1	rs7248508	0.522744	0.526958747465	0.685404424473	0.728029336735	0.352247807018	0.776672496721	0.453231381586	0.406255640183	0.486462728551	0.596900776808	190609063506732,203395363506733,206865653506734,208819603506735,224846277709335,224792027709336	19060906,20339536,20686565,20881960,22484627,22479202	LDL cholesterol(0.0152),HDL cholesterol(0.0279),Triglycerides(0.0141),Height(0.0104),Obesity with early age of onset (age >2)(0.0471),Adiponectin levels(0.0294)	../MuPIT_Interactive?gm=chr19:17205973										0.631589				12243.8	.	hom	812	406	2.0		
-10	VAR526_unknown	chr19	18856059	+	C	T	unknown	UPF1	MS	ENST00000599848.5	+	EAIDSPVSFLALHNQIR	EAIDSPVSFLVLHNQIR	A571V	ENST00000262803.9:A560V(MS),*ENST00000599848.5:A571V(MS)							ENST00000262803	p.A560V (large_intestine 1)	1	0	0	NC_000019.10:g.18856059C>T	ENST00000599848.5:p.Ala571Val	ENST00000262803.9:p.Ala560Val,*ENST00000599848.5:p.Ala571Val	0			ENST00000262803.9:A560V	0.09372	0.662						ENST00000599848.5:A571V(0.643:0.10292),*ENST00000262803.9:A560V(0.662:0.09372)		COSM3100527	large_intestine(1)	1		0.0													../MuPIT_Interactive?gm=chr19:18856059										0				10269.5	.	het	592	2379	0.248844052123