Mercurial > repos > waqas > macaron
changeset 0:c9636a827049 draft default tip
Uploaded
| author | waqas |
|---|---|
| date | Wed, 12 Sep 2018 08:45:03 -0400 |
| parents | |
| children | |
| files | MACARON-GenMed-LabEx/LICENSE.txt MACARON-GenMed-LabEx/MACARON MACARON-GenMed-LabEx/MACARON_validate.sh MACARON-GenMed-LabEx/README.md MACARON-GenMed-LabEx/_config.yml MACARON-GenMed-LabEx/demo/MACARON_output.txt MACARON-GenMed-LabEx/demo/MACARON_validate.txt MACARON-GenMed-LabEx/demo/sub1.chr22_21349676-21349677.sample02.bam MACARON-GenMed-LabEx/demo/variants_of_interest.vcf MACARON-GenMed-LabEx/index.html |
| diffstat | 10 files changed, 1385 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/LICENSE.txt Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,64 @@ +GNU LESSER GENERAL PUBLIC LICENSE +Version 3, 29 June 2007 + +Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/> + +Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. + +This version of the GNU Lesser General Public License incorporates the terms and conditions of version 3 of the GNU General Public License, supplemented by the additional permissions listed below. +0. Additional Definitions. + +As used herein, “this License” refers to version 3 of the GNU Lesser General Public License, and the “GNU GPL” refers to version 3 of the GNU General Public License. + +"The Library" refers to a covered work governed by this License, other than an Application or a Combined Work as defined below. + +An “Application” is any work that makes use of an interface provided by the Library, but which is not otherwise based on the Library. Defining a subclass of a class defined by the Library is deemed a mode of using an interface provided by the Library. + +A “Combined Work” is a work produced by combining or linking an Application with the Library. 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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/MACARON Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,560 @@ +#!/usr/bin/python + +#alpha version 0.7 (05/09/18) + +""" +#Script to identify SNPs located within a genetic codon: + +Annotation of SNPs (including synonymous and non-synonymous variants) located within the same genetic codon requires attention. This idea conflicts with the annotations observed by traditional annotation software widely used now a days. While looking at the combined effect within the framework of genetic codon, we have new / altered codons that code for new amino acid that can be predicted by using this MACARON python script. + +#####------How to run quickly run MACARON------- + +# python MACARON -i yourinputfile.vcf + +# python MACARON -i /path/to/yourinputfile.vcf -o /path/to/MACARON_output.txt -f (INFO)_FIELD_HEADER --GATK /path/to/GenomeAnalysisTK.jar --HG_REF /path/to/hg.fasta --SNPEFF /path/to/snpeff.jar --SNPEFF_HG hg19 + +# python MACARON -i yourinputfile.vcf -o MACARON_output.txt --gatk4 (when using gatk versions >= 4.0) + +""" + +import sys, os, time +import itertools +import multiprocessing +import re +import subprocess +from argparse import ArgumentParser + +## GLOBAL VARIABLES (IMPORTANT: You can set the default values here) +GATK="/home/wuk/software/GenomeAnalysisTK.jar" +#GATK="/home/wuk/software/gatk-4.0.1.2/gatk-package-4.0.1.2-local.jar" +HG_REF="/home/wuk/Working/gnme_refrnces/Homo_sapiens_assembly19.fasta" +SNPEFF="/home/wuk/software/snpEff/snpEff.jar" +SNPEFF_HG="GRCh37.75" ## SnpEff human genome annotation database version + +## PRINTINGS, AESTHETICS +str_progress_list = ["\tIndexing VCF file", + "\tIdentifying SnpClusters", + "\tExtracting SnpClusters", + "\tAnnotating SnpClusters", + "\tExcluding InDels", + "\tGenerating a SnpCluster Table", + "\tRe-annotating Codons", + "\tRemoving SnpCluster if AA_Change_pcSNV == (AA1 or AA2)", + "\tExtracting established SnpClusters - for which two (or three) SNPs are reference heterozygous (or non-reference homozygous)"] +header = ("\n" + + "(###############)\n" + + "@@@@ MACARON @@@@\n" + + "(###############)\n\n" + + "Starting....\n") +footer = "\nMACARON Run Completed. Bon Courage with Analysis ...,,,!!!!\n" + +def animate(keep_anim, idx): + c = "|/-\\" + i=0 + while keep_anim.is_set(): + i += 1 + sys.stdout.write("\r>" + str_progress_list[idx] + ": " + c[i % len(c)] +"\r") + sys.stdout.flush() + time.sleep(0.1) + sys.stdout.write("\r " + str_progress_list[idx] + ": Done!\n") +def print_step(keep_anim, idx): + if not(ECO): + keep_anim.set() + anim_thread = multiprocessing.Process(target=animate, args=(keep_anim, idx)) + anim_thread.start() + return anim_thread + else: + sys.stdout.write(">" + str_progress_list[idx] + ": in progress...\r" ) + sys.stdout.flush() + return None +def end_print_step(keep_anim, anim_thread, idx): + if not(ECO): + keep_anim.clear(); anim_thread.join() + else: + sys.stdout.write(" " + str_progress_list[idx] + ": Done! \n") + sys.stdout.flush() + + +## CLASS DEFINITIONS + +class fileHandler: + def __init__(self): + self.data = []; + def open_file(self, readfl): + self.rfile = open(readfl, 'r').readlines() + return self.rfile + def write_file(self, writefl): + self.wfile = open(writefl, 'w') + return self.wfile + +class SearchDB(fileHandler): + def __init__(self): + self.data = [] + from collections import defaultdict + self.ident_ranges_HMBM = defaultdict(list) + def Search_CODON(self, vcf_input, workdir, FIELDS): + """ + Calling SNPClusters + + USAGE INSTRUCTIONS: Full path to the software directories should be set before compiling. + """ + + ####################### + Fld_Len = int(len(FIELDS.split(","))) + FldwithF = " ".join(["-F " + str(x) for x in FIELDS.split(",")]) + + ## Options compatible with GATK versions >= 4.0: add option --gatk4 when calling MACARON + if GATK4: + GATK_v, SNPeff_v = (" ", " -v ") if VERBOSE else (" --QUIET true --verbosity ERROR ", " ") + cmd0 = "java -Xmx12g -jar " + GATK + " IndexFeatureFile -F " + vcf_input + GATK_v + cmd1 = "java -Xmx12g -jar " + GATK + " VariantFiltration -R " + HG_REF + " -V "+ vcf_input +" -O " + workdir + "snp_clsters2_ws3.vcf --cluster-size 2 --cluster-window-size 3" + GATK_v + cmd2 = "java -Xmx12g -jar " + GATK + " SelectVariants -R " + HG_REF + " -V " + workdir + "snp_clsters2_ws3.vcf -O " + workdir + "snp_clsters2_ws3_clstronly.vcf -select 'FILTER == SnpCluster'" + GATK_v + cmd3 = "java -Xmx12g -jar " + SNPEFF + SNPeff_v + SNPEFF_HG + " -formatEff -lof -classic " + workdir + "snp_clsters2_ws3_clstronly.vcf > " + workdir + "snp_clsters2_ws3_clstronly_annt.vcf" + cmd4 = "java -Xmx12g -jar " + GATK + " SelectVariants -R " + HG_REF + " -V " + workdir + "snp_clsters2_ws3_clstronly_annt.vcf -O " + workdir + "snp_clsters2_ws3_clstronly_annt_snv.vcf --select-type-to-include SNP" + GATK_v + cmd5 = "java -Xmx12g -jar " + GATK + " VariantsToTable -R " + HG_REF + " -V " + workdir + "snp_clsters2_ws3_clstronly_annt_snv.vcf -F CHROM -F POS -F ID -F REF -F ALT -F EFF " + FldwithF + " -GF GT --error-if-missing-data --show-filtered -O " + workdir + "snp_clsters2_ws3_clstronly_annt_snv_clstronly.table" + GATK_v + ## GATK4 needs to index the VCF upfront + thread = print_step(keep_anim, 0) + subprocess.check_output(cmd0, shell=True) + end_print_step(keep_anim, thread, 0) + + else: ## Options comptatible with GATK versions < 4 + GATK_v, SNPeff_v = (" ", " -v ") if VERBOSE else (" --logging_level ERROR ", " ") + cmd1 = "java -Xmx4g -jar " + GATK + " -T VariantFiltration -R " + HG_REF + " -V " + vcf_input + " -o " + workdir + "snp_clsters2_ws3.vcf --clusterSize 2 --clusterWindowSize 3" + GATK_v + cmd2 = "java -Xmx4g -jar " + GATK + " -T SelectVariants -R " + HG_REF + " -V " + workdir + "snp_clsters2_ws3.vcf -o " + workdir + "snp_clsters2_ws3_clstronly.vcf -select 'FILTER == SnpCluster'" + GATK_v + cmd3 = "java -Xmx4g -jar " + SNPEFF + SNPeff_v + SNPEFF_HG + " -formatEff -lof -classic " + workdir + "snp_clsters2_ws3_clstronly.vcf > " + workdir + "snp_clsters2_ws3_clstronly_annt.vcf" + cmd4 = "java -Xmx4g -jar " + GATK + " -T SelectVariants -R " + HG_REF + " -V " + workdir + "snp_clsters2_ws3_clstronly_annt.vcf -o " + workdir + "snp_clsters2_ws3_clstronly_annt_snv.vcf --selectTypeToInclude SNP" + GATK_v + cmd5 = "java -Xmx4g -jar " + GATK + " -T VariantsToTable -R " + HG_REF + " -V " + workdir + "snp_clsters2_ws3_clstronly_annt_snv.vcf -F CHROM -F POS -F ID -F REF -F ALT -F EFF " + FldwithF + " -GF GT --showFiltered -o " + workdir + "snp_clsters2_ws3_clstronly_annt_snv_clstronly.table" + GATK_v + + thread = print_step(keep_anim, 1) + subprocess.check_output(cmd1, shell=True) + end_print_step(keep_anim, thread, 1) + thread = print_step(keep_anim, 2) + subprocess.check_output(cmd2, shell=True) + end_print_step(keep_anim, thread, 2) + thread = print_step(keep_anim, 3) + subprocess.check_output(cmd3, shell=True) + end_print_step(keep_anim, thread, 3) + thread = print_step(keep_anim, 4) + subprocess.check_output(cmd4, shell=True) + end_print_step(keep_anim, thread, 4) + thread = print_step(keep_anim, 5) + subprocess.check_output(cmd5, shell=True) + end_print_step(keep_anim, thread, 5) + + subprocess.check_output("rm snpEff_genes.txt", shell=True) + subprocess.check_output("rm snpEff_summary.html", shell=True) + + ####-------------------------------------- + + def Change_zygo(ref, alt, zyg): + """ + program to convert zygosity code ref/alt to 0/1. + Input Variables: + + ref = "A";alt = "G" + zyg = ['A/G', 'G/A', 'G/G', 'A/A', './.', 'G/.', './G', './A', 'A/.'] + chzyg = ['0/1', '1/0', '1/1', '0/0', './.', '1/.', './1', './0', '0/.'] + InputUsage Variables: + chgz = Change_zygo(ref, alt, zyg) + + """ + import re + chg_zyg = {}; i = 1 + for cs in zyg: + csp = re.split('[|/]', cs) + if ((ref == csp[0]) and (ref == csp[1]) and ((csp[0] != ".") and (csp[1] != "."))): + chg_zyg[i] = "0/0" + elif ((ref != csp[0]) and (ref == csp[1]) and ((csp[0] != ".") and (csp[1] != "."))): + chg_zyg[i] = "1/0" + elif ((ref == csp[0]) and (ref != csp[1]) and ((csp[0] != ".") and (csp[1] != "."))): + chg_zyg[i] = "0/1" + elif ((ref != csp[0]) and (ref != csp[1]) and ((csp[0] != ".") and (csp[1] != "."))): + chg_zyg[i] = "1/1" + elif ((csp[0] == ".") and (csp[1] == ".")): + chg_zyg[i] = cs + elif ((csp[1] == ".")): + if (ref == csp[0]): + chg_zyg[i] = "0/." + elif (ref != csp[0]): + chg_zyg[i] = "1/." + elif ((csp[0] == ".")): + if (ref == csp[1]): + chg_zyg[i] = "./0" + elif (ref != csp[1]): + chg_zyg[i] = "./1" + i += 1 + return list(chg_zyg.values()) + ####-------------------------------------- + + with open(workdir + "snp_clsters2_ws3_clstronly_annt_snv_clstronly.table", 'r') as f1, open(workdir + "temp_file1", 'w') as output: + first_line = f1.readline().strip() + zyg_head = '\t'.join(first_line.split()[6+Fld_Len:]) + output.write(first_line + "\t" + zyg_head + "\t" + str("Protein_coding_EFF AA-Change REF-codon ALT-codon") + "\n") + for line in f1: + line1 = line.strip() + line_TAB = line1.split("\t") + line_EFF = line_TAB[5].split("|") + if (len(line_EFF) > 1): + if ((line_EFF[1] == "SILENT") or (line_EFF[1] == "MISSENSE") or (line_EFF[1] == "NONSENSE")): + True + linesp = line_EFF[2].split("/") + ref = line_TAB[3] + alt = line_TAB[4] + zyg = line_TAB[6+Fld_Len:] + chgz = Change_zygo(ref, alt, zyg) + chgz_out = '\t'.join(chgz) + wrt = str(line_EFF[1] + "\t" + line_EFF[3] + "\t" + linesp[0] + "\t" + linesp[1]) + output.write(line1 + "\t" + chgz_out + "\t" + wrt + "\n") + return None + + ##------------------------------- + import string + gencode = {'ATA':'I', 'ATC':'I', 'ATT':'I', 'ATG':'M', 'ACA':'T', 'ACC':'T', 'ACG':'T', 'ACT':'T','AAC':'N', 'AAT':'N', 'AAA':'K', 'AAG':'K', 'AGC':'S', 'AGT':'S', 'AGA':'R', 'AGG':'R','CTA':'L', 'CTC':'L', 'CTG':'L', 'CTT':'L', 'CCA':'P', 'CCC':'P', 'CCG':'P', 'CCT':'P','CAC':'H', 'CAT':'H', 'CAA':'Q', 'CAG':'Q', 'CGA':'R', 'CGC':'R', 'CGG':'R', 'CGT':'R','GTA':'V', 'GTC':'V', 'GTG':'V', 'GTT':'V', 'GCA':'A', 'GCC':'A', 'GCG':'A', 'GCT':'A','GAC':'D', 'GAT':'D', 'GAA':'E', 'GAG':'E', 'GGA':'G', 'GGC':'G', 'GGG':'G', 'GGT':'G','TCA':'S', 'TCC':'S', 'TCG':'S', 'TCT':'S', 'TTC':'F', 'TTT':'F', 'TTA':'L', 'TTG':'L','TAC':'Y', 'TAT':'Y', 'TAA':'_', 'TAG':'_', 'TGC':'C', 'TGT':'C', 'TGA':'_', 'TGG':'W'} + + # a function to translate a single codon + def translate_codon(self, codon): + return self.gencode.get(codon.upper(), '#') + # a function to split a sequence into codons + def split_into_codons(self, dna, frame): + codons = [] + for i in range(frame-1, len(dna)-2, 3): + codon = dna[i:i+3] + codons.append(codon) + return codons + # a function to translate a dna sequence in a single frame + def translate_dna_single(self, dna, frame=1): + codons = self.split_into_codons(dna, frame) + amino_acids = '' + for codon in codons: + amino_acids = amino_acids + self.translate_codon(codon) + return amino_acids + + def TWO_VAR(self, workdir): + """ + ###---Two variants (2VAR) codon changes--- + ##---------------------------------- + """ + lines = open(workdir + "temp_file1", "r").read().splitlines() + writ2 = self.write_file(workdir + "temp_file2") + #--- + midline_head = lines[0].strip().split("\t") + try: + midline_headcrp = '\t'.join([w.replace(midline_head[5], 'Gene_Name') for w in midline_head]) + except ValueError: + pass + writ2.write(str(midline_headcrp + "\t" + "ALT-codon_merge-2VAR" + "\t" + "AA-Change-2VAR") + "\n") + #--- + + i=0; TRcode =""; protcode = ""; midline_crpit = "" + for i in range(len(lines)): + #--- + midline_crp = lines[i].strip().split("\t") + try: + if len(midline_crp[5].split("|")) != 1: + GeneName = midline_crp[5].split("|")[5] + midline_crpit = '\t'.join([w.replace(midline_crp[5], GeneName) for w in midline_crp]) + except ValueError: + pass + #--- + try: + beforeline = lines[i-1].strip() + line0 = beforeline.split("\t")[-3] + beforeline1 = re.findall("\d+", line0) + + midline = lines[i].strip() + line1 = midline.split("\t")[-3] + midline1 = re.findall("\d+", line1) + + nextline = lines[i+1].strip() + line2 = nextline.split("\t")[-3] + nextline1 = re.findall("\d+", line2) + #----Condition to replace empty list ([] to ['000']) produced from the header column "AA-Change". + if (line0 == "AA-Change"): + beforeline1.append('000') + elif (line1 == "AA-Change"): + midline1.append('000') + elif (line2 == "AA-Change"): + nextline1.append('000') + #---- + REFbf=[]; line22="" + if ((beforeline1[0] == midline1[0]) or (midline1[0] == nextline1[0])): + spREFbf=[]; lscod1=[]; lscod2=[] + REF= lines[i].strip().split("\t")[-2] + if (midline1[0] == beforeline1[0]): + REFbf = lines[i-1].strip().split("\t")[-2] + + line11 = lines[i].strip().split("\t")[-1] + if (midline1[0] == nextline1[0]): + line22 = lines[i+1].strip().split("\t")[-1] + if REFbf != []: + for cod in REFbf: + spREFbf.append(cod) + for cod in line11: + lscod1.append(cod) + for cod in line22: + lscod2.append(cod) + + if (((lscod1[0].islower()==True and lscod2[0].islower()==True) or (lscod1[1].islower()==True and lscod2[1].islower()==True) or (lscod1[2].islower()==True and lscod2[2].islower()==True)) and ((lscod1[0] == lscod2[0]) or (lscod1[1] == lscod2[1]) or (lscod1[2] == lscod2[2]))): + threeltr_code = [] + if ((lscod1[0].isupper()==True and lscod2[0].islower()==True) or (lscod1[0] == lscod2[0])): + threeltr_code.append(lscod1[0]) + elif((lscod1[0].islower()==True and lscod2[0].isupper()==True) or (lscod1[0] == lscod2[0])): + threeltr_code.append(lscod2[0]) + + if((lscod1[1].isupper()==True and lscod2[1].islower()==True) or (lscod1[1] == lscod2[1])): + threeltr_code.append(lscod1[1]) + elif((lscod1[1].islower()==True and lscod2[1].isupper()==True) or (lscod1[1] == lscod2[1])): + threeltr_code.append(lscod2[1]) + + if((lscod1[2].isupper()==True and lscod2[2].islower()==True) or (lscod1[2] == lscod2[2])): + threeltr_code.append(lscod1[2]) + elif((lscod1[2].islower()==True and lscod2[2].isupper()==True) or (lscod1[2] == lscod2[2])): + threeltr_code.append(lscod2[2]) + #----------------------- + if(len(threeltr_code)==3): + TRcode = ''.join(threeltr_code) + else: + TRcode = 'Multiallelic-t1' + #----------------------- + else: + TRcode = '...' + + if(TRcode != line22): + protcode = self.translate_dna_single(TRcode) + else: + TRcode = "." + + if (REF == REFbf): + protcode = "#####";TRcode = "Multiallelic-t2" + writ2.write(str(midline_crpit + "\t" + TRcode + "\t" + protcode) + "\n") + + except IndexError: + if not midline_crpit.split("\t")[0] == "CHROM": + writ2.write(str(midline_crpit + "\t" + "." + "\t" + protcode) + "\n") + pass + return None + + def THREE_VAR(self, workdir): + """ + ###---Three variants (3VAR) codon changes--- + ##---------------------------------- + """ + lines = open(workdir + "temp_file2", "r").read().splitlines() + writ3 = self.write_file(workdir + "temp_file3") + #--- + midline_head =lines[0].strip() + writ3.write(str(midline_head + "\t" + "ALT-codon_merge-3VAR" + "\t" + "AA-Change-3VAR") + "\n") + #--- + i = 0; TRcode = ""; protcode = "" + for i in range(len(lines)): + try: + #--- + midline_crp = lines[i].strip() + #--- + beforeline = lines[i-1].strip() + line0 = beforeline.split("\t")[-5] + beforeline1 = re.findall("\d+", line0) + midline = lines[i].strip() + line1 = midline.split("\t")[-5] + midline1 = re.findall("\d+", line1) + nextline = lines[i+1].strip() + line2 = nextline.split("\t")[-5] + nextline1 = re.findall("\d+", line2) + + line11=[]; line22=[]; writelst= [] + if ((beforeline1[0] == midline1[0]) or (midline1[0] == nextline1[0])): + lscod1=[]; lscod2=[] + line11 = lines[i].strip().split("\t")[-2] + if (midline1[0] == nextline1[0]): + line22 = lines[i+1].strip().split("\t")[-2] + for cod in line11: + lscod1.append(cod) + for cod in line22: + lscod2.append(cod) + #----------------------- + if(len(lscod1) == 3 and len(lscod2) == 3): + threeltr_code = []; + + if ((lscod1[0].isupper()==True) and (lscod2[0].islower()==True) or + (lscod1[0].isupper()==True and lscod2[0].isupper()==True)): + threeltr_code.append(lscod1[0]) + elif ((lscod1[0].islower()==True) and (lscod2[0].isupper()==True)): + threeltr_code.append(lscod2[0]) + + if ((lscod1[1].isupper()==True) and (lscod2[1].islower()==True) or + (lscod1[1].isupper()==True and lscod2[1].isupper()==True)): + threeltr_code.append(lscod1[1]) + elif ((lscod1[1].islower()==True) and (lscod2[1].isupper()==True)): + threeltr_code.append(lscod2[1]) + + if ((lscod1[2].isupper()==True) and (lscod2[2].islower()==True) or + (lscod1[2].isupper()==True and lscod2[2].isupper()==True)): + threeltr_code.append(lscod1[2]) + elif ((lscod1[2].islower()==True) and (lscod2[2].isupper()==True)): + threeltr_code.append(lscod2[2]) + #----------------------- + if(len(threeltr_code) == 3): + TRcode = ''.join(threeltr_code) + else: + TRcode = 'Multiallelic-t1' + #----------------------- + else: + TRcode = '.' + + if(TRcode != line22): + protcode = self.translate_dna_single(TRcode) + if len(protcode) == 0: + protcode = "."; TRcode = "." + else: + TRcode = "." + + if protcode == "" or TRcode == "": + protcode = "."; TRcode = "." + #----------------------- + writ3.write(str(midline_crp + "\t" + TRcode + "\t" + protcode) + "\n") + + ##---------------------- + except IndexError: + if not midline_crp.split("\t")[0] == "CHROM": + if len(protcode) ==0: + protcode = "."; TRcode = "." + writ3.write(str(midline_crp + "\t" + TRcode + "\t" + protcode) + "\n") + else: + protcode = "."; TRcode = "." + writ3.write(str(midline_crp + "\t" + TRcode + "\t" + protcode) + "\n") + pass + return None + + def PARS_OUT_VAR(self, workdir): + """ + ###---Pars variants (2VAR _ 3VAR) based on change of protein codons --- + ##---------------------------------- + """ + #This first records the ones that do match and saves the value in column 3 (less the final matching amino acid residue). + subprocess.check_output("awk 'index($(NF-6), $(NF-2)) {print}' " + workdir + "temp_file3 | awk '{print $(NF-6)}' | sed s'/.$//' > " + workdir + "matches.list", shell=True) + + #This then searches for the ones that do not match, and then also eliminates any value recorded in matches.list + subprocess.check_output("awk '!index($(NF-6), $(NF-2)) { print }' " + workdir + "temp_file3 | grep -w -v -f " + workdir + "matches.list | awk -F'\t' '{ print }' > " + workdir + "temp_file4", shell=True) + + return None + + def ZYGO_PAIR(self, macaron_output, workdir, FIELDS): + """ + ###---Pair of zygosity check: remove pair of codons for which one SNP is reference homozygous --- + ##---------------------------------- + """ + + Fld_Len = int(len(FIELDS.split(","))) + lines = open(workdir + "temp_file4", "r").read().splitlines() + writ4 = self.write_file(macaron_output) + #--- + midline_head = lines[0].strip() + writ4.write(str(midline_head) + "\n") + #--- + nextline_pos_lst = [] + + for i in range(len(lines)): + #--- + midline_crp = lines[i].strip() + #--- + beforeline = lines[i-1].strip() + beforeline_pos = re.findall("\d+", beforeline.split("\t")[-7]) + midline = lines[i].strip() + midline_pos = re.findall("\d+", midline.split("\t")[-7]) + try: + nextline = lines[i+1].strip() + nextline_pos =re.findall("\d+", nextline.split("\t")[-7]) + ##------- + if (midline_pos[0] == nextline_pos[0]): + Start_lns = int(6) + Fld_Len + End_lns = int(8) + Start_zyg_lns = int(len(midline.split("\t")) - int(Start_lns)) + midline_zyg = midline.split("\t")[-int(Start_zyg_lns):-int(End_lns)] + nextline_zyg = nextline.split("\t")[-int(Start_zyg_lns):-int(End_lns)] + checkList = list(['0/1:1/0', '1/0:0/1', '1/0:1/0', '0/1:0/1', '1/0:1/1', '1/1:1/0', '0/1:1/1', '1/1:0/1', '1/1:1/1']) + Mergetwozyg = ','.join([str(a) + ":" + b for a,b in zip(midline_zyg, nextline_zyg)]) + Mergetwozygsp = Mergetwozyg.split(",") + if set(Mergetwozygsp).intersection(checkList) != set([]): + if ((midline_pos[0] == nextline_pos[0]) and (midline_pos[0] == beforeline_pos[0])): + writ4.write(str(nextline)+"\n") + else: + writ4.write(str(midline+"\n"+nextline)+"\n") + ##------- + except IndexError: + #Condition to remove the duplicated line at the end and prints only paired lines. + nextline_pos_lst.append(nextline_pos[0]) + result = dict((i, nextline_pos_lst.count(i)) for i in nextline_pos_lst) + if len(result) == 1: + writ4.write(str(nextline) + "\n") + + return None + ###------ + + +## MACARON MAIN +if __name__ == "__main__": + ## Parsing arguments + parser = ArgumentParser(description="-Script to identify SnpClusters (SNPs within the same genetic codon)") + parser.add_argument("-i", "--infile", dest="INPUTFile",default=False, required=True, help="Full path of the input VCF file.") + parser.add_argument("-o", "--outfile", dest="OUTPUTFile",default="./MACARON_output.txt", required=False, help="Path of the output txt file (Default Output file: MACARON_output.txt)") + parser.add_argument("-f", "--fields", dest="Fields", default="QUAL", required=False, help=" Single field name or comma-seperated ',' multiple field names can be given. Field name should be given according to the (INFO) field header of the input vcf file. Example: -f Func.refGene,ExonicFunc.refGene,Gene.refGene,1000g2015aug_all,ExAC_ALL,ExAC_EAS,clinvar_20161128,gnomAD_exome_ALL,gnomAD_genome_ALL,EFF,CSQ") + parser.add_argument("--GATK", dest="GATK_path", default=GATK, required=False, help="Indicate the full path to GATK jar file") + parser.add_argument("--HG_REF", dest="HG_REF_path", default=HG_REF, required=False, help="Indicate the full path to the reference genome fasta file") + parser.add_argument("--SNPEFF", dest="SNPEFF_path", default=SNPEFF, required=False, help="Indicate the full path to SnpEff jar file") + parser.add_argument("--SNPEFF_HG", dest="SNPEFF_HG_version", default=SNPEFF_HG, required=False, help="Indicate SnpEff human genome annotation database version") + parser.add_argument("--gatk4", dest="GATK4", default=False, required=False, action='store_true', help="Add this option when using GATK versions >= 4.0") + parser.add_argument("-v", "--verbosity", dest="Verbosity", default=False, required=False, action='store_true', help="Use to print verbosity (Mostly GATK/SNPEFF output)") + parser.add_argument("-c", "--eco_friendly", dest="ECO", default=False, required=False, action='store_true', help="Save a thread, but you won't be able to stare at the fabulous animation while waiting ...") + + ## Assign arguments to global variables + args = parser.parse_args() + FIELDS = args.Fields + GATK4 = args.GATK4 + VERBOSE = args.Verbosity + GATK = args.GATK_path + HG_REF = args.HG_REF_path + SNPEFF = args.SNPEFF_path + SNPEFF_HG = args.SNPEFF_HG_version + ECO = args.ECO + + ## Inputs / Outputs path & names + INF = args.INPUTFile + OUTF = args.OUTPUTFile + TMPDIR = os.path.dirname(os.path.abspath(OUTF)) + "/macaron_tmp/" + subprocess.check_output("mkdir -p " + TMPDIR, shell=True) + + ######################## + ## MAIN PROCESS ## + ######################## + print(header) + + ## Check if global variables point to existing files: + INF_check = os.path.exists(INF) + GATK_check = os.path.exists(GATK) + HG_REF_check = os.path.exists(HG_REF) + SNPEFF_check = os.path.exists(SNPEFF) + SNPEFF_HG_non_empty = (SNPEFF_HG != "") + if not(INF_check and GATK_check and HG_REF_check and SNPEFF_check and SNPEFF_HG_non_empty): + print(">ERROR : One or several global variable: \n VCF={} > {}\n GATK={} > {}\n HG_REF={} > {}\n SNPEFF={} > {}\n SNPEFF_HG={} > {}\n>Please correct and try again!".format(INF, INF_check, GATK, GATK_check, HG_REF, HG_REF_check, SNPEFF, SNPEFF_check, SNPEFF_HG, SNPEFF_HG_non_empty)) + sys.exit(1) + else: ## If everything checks out, start MACARON + ## Animation event initialization + keep_anim = multiprocessing.Event() + + ## 1)VARIANTS FILTERING, ANNOTATION (GATK,SNPEff) + clF1 = SearchDB().Search_CODON(INF, TMPDIR, FIELDS) + ## 2)SEARCH MULTI-SNPS CODONS + thread = print_step(keep_anim, 6) + clF2 = SearchDB().TWO_VAR(TMPDIR) + clF3 = SearchDB().THREE_VAR(TMPDIR) + end_print_step(keep_anim, thread, 6) + ## 3)CHECK IF SNPCLUSTERS IMPACT CODON + thread = print_step(keep_anim, 7) + clF4 = SearchDB().PARS_OUT_VAR(TMPDIR) + end_print_step(keep_anim, thread, 7) + ## 4) EXTRACT SNPCLUSTERS (Keeping SnpCluster if >=1 sample is Ref-Heterozygous or nonRef-Homozygous) + thread = print_step(keep_anim, 8) + clF5 = SearchDB().ZYGO_PAIR(OUTF, TMPDIR, FIELDS) + end_print_step(keep_anim, thread, 8) + print(footer) + subprocess.check_output("rm -r " + TMPDIR, shell=True)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/MACARON_validate.sh Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,49 @@ +#!/bin/bash + +#sub1.chr22_21349676-21349677.sample02.bam + +bam=$1; +name=$(echo $bam | cut -d'.' -f1) +region=$(echo $bam | cut -d'.' -f2) +sample=$(echo $bam | cut -d'.' -f3) + +chr=$(echo $region | cut -d'_' -f1) +pos=$(echo $region | cut -d'_' -f2) + +beg=$(echo $pos | cut -d'-' -f1) +end=$(echo $pos | cut -d'-' -f2) + +#beg=$(($beg+50)) +#end=$((end-50)) + +#echo "name $name" +#echo "region $region" +#echo "sample $sample" + +echo "$name $chr:$beg-$end $sample" +echo "$name $chr:$beg-$end $sample" >> MACARON_validate.txt + +samtools view $bam | awk -v start=$beg -v stop=$end ' +{ + pos=$4; + if(pos < start){ + cstart=1+start-pos; + cstop=1+stop-pos; + print cstart"."cstop"."$10; + } +}' > tmp + +while read line; +do + cb=$(echo $line | cut -d'.' -f1); + ce=$(echo $line | cut -d'.' -f2); + seq=$(echo $line | cut -d'.' -f3); + echo $seq | cut -c$cb-$ce; +done <tmp | sort | uniq -c | sort -n >> MACARON_validate.txt +rm tmp + + + + +exit 0 +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/README.md Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,286 @@ +MACARON User Guide +================ + +# Table of Contents + +[//]: # (BEGIN automated TOC section, any edits will be overwritten on next source refresh) + +* [Introduction](#introduction) +* [Installation](#installation) + * [Operating System Guidelines](#operating-system-guidelines) + * [Runtime Pre-requisite](#runtime-pre-requisite) + * [Software Dependencies](#software-dependencies) + * [Downloading the Source Code](#downloading-the-source-code) + * [Contents of the Folder MACARON_GenMed](#contents-of-the-folder-macaron_genmed) +* [Running the MACARON](#running-the-macaron) + * [Input Requirements](#input-requirements) + * [Default Options](#default-options) + * [demo Folder](#demo-folder) + * [Advanced Options](#advanced-options) +* [MACARON Reporting Format](#macaron-reporting-format) +* [Validating SNVs Existed on the Same Reads](#validating-snvs-existed-on-the-same-reads) +* [References](#references) +* [Citation](#citation) + +[//]: # (END automated TOC section, any edits will be overwritten on next source refresh) + +# Introduction + +MACARON (Multi-bAse Codon-Associated variant Re-annotatiON) is a python framework to identify and re-annotate multi-base affected codons in whole genome/exome sequence data. Starting from a standard VCF file, MACARON identifies, re-annotates and predicts the amino acid change resulting from multiple single nucleotide variants (SNVs) within the same genetic codon. + +The information below includes how to install and run MACARON to filter a list of variant records (from VCF file) called by any existing SNP-based variant caller to identify SNVs with the same genetic codon and correct their corresponding amino acid change. + +See latest [News](https://github.com/waqasuddinkhan/MACARON-GenMed-LabEx/wiki/News???) and [Updates](https://github.com/waqasuddinkhan/MACARON-GenMed-LabEx/wiki#updates) on [MACARON-GenMed-LabEx Wiki page](https://github.com/waqasuddinkhan/MACARON-GenMed-LabEx/wiki). + +# Installation + +### Operating System Guidelines + +MACARON is know to run on LINUX UBUNTU 16.04 LTS. However, MACARON can be run on any other LINUX version. + +### Runtime Pre-requisite + +__1.__ MACARON is executable in __PYTHON v2.7 or later__. If the user has multiple PYTHON versions, please make sure that your running environment is set to the required version of PYTHON. + +__2.__ Check your __JAVA__ version as MACARON is tested with: + + java -version + openjdk version __"1.8.0_151"__ + OpenJDK Runtime Environment (build 1.8.0_151-8u151-b12-0ubuntu0.16.04.2-b12) + OpenJDK 64-Bit Server VM (build 25.151-b12, mixed mode) + +### Software Dependencies + +Before running MACARON, please make sure that following software are installed properly: + +__1.__ __Genome-Analysis Toolkit__ (https://software.broadinstitute.org/gatk/download/). + +__2.__ __SnpEff__ (tested with __v4.3__ (build 2017-05-05 18:41). However, MACARON can also run with any older or newer version (http://snpeff.sourceforge.net/download.html). + +__3.__ __SAMTools__ (tested with version __0.1.19__), however any version can be used. + +__4.__ __Human Reference Genome__: Depends on user’s input. + +__5.__ __SnpEff’s Human Annotation Database__: Depends on user’s input. + +For __1__ and __2__, as long as they are compatible with JAVA, MACARON has no issues. + +### Downloading the Source Code + +The most prefered way to use the lastest version of MACARON is: + + git clone https://github.com/waqasuddinkhan/MACARON-GenMed-LabEx.git + +or download the ZIP folder. + +MACARON source code can also be downloaded from http://www.genmed.fr/images/publications/data/MACARON_GenMed.zip + +After acquiring a release distribution of the source code, the build procedure is to unpack the zip file: + + unzip MACARON_GenMed.zip + +### Contents of the folder MACARON_GenMed + +* *MACARON* – The MACARON python code +* *MACARON_validate.sh* – a BASH-shell script to validate multi-SNVs located on the same read that affect the same genetic codon + +# Running the MACARON + +### Input Requirements + +Before running MACARON, check these __input technical notes__ as the following limitations exist for either the input VCF file, or the required software dependencines: + +* Chromosome (chr) notation should be compatible with both input VCF file and Human Reference Genome file, or vice versa, + +* Sequence dictionaries of input VCF file and Human Reference Genome file should be the same, + +* Input VCF file (should) suitably be annotated with ANNOVAR, and additionally with any other annotation software, e.g, VEP (https://www.ensembl.org/info/docs/tools/vep/index.html) if the user has a desire to get the full functionality of -f option (see [Advanced Options](#advanced-options) below), + +* Same Human Reference Genome file should be used for MACARON which is practiced earlier for alignemnt and (or) to call variant sets, + +* Versions of input VCF file, Human Reference Genome file and SnpEff database file should be the same (hg19 / GRCh37 = SnpEff GRCh37.75) or (hg38 / GRCh38 = SnpEff GRCh38.86). + +### Default Options + +For a full list of MACARON executable options, run: + + python MACARON -h + +By default, MACARON depends on the `GLOBAL VARIABLES` set in the script before run: + + ## GLOBAL VARIABLES (IMPORTANT: You can set the default values here) + GATK="/home/wuk/software/GenomeAnalysisTK.jar" + #GATK="/home/wuk/software/gatk-4.0.1.2/gatk-package-4.0.1.2-local.jar" + HG_REF="/home/wuk/Working/gnme_refrnces/Homo_sapiens_assembly19.fasta" + SNPEFF="/home/wuk/software/snpEff/snpEff.jar" + SNPEFF_HG="GRCh37.75" ## SnpEff genome version + +To run MACARON with __GATK <4.0__ versions, simply type: + + python MACARON -i test_input.vcf + +If running with __GATK >= 4.0__ versions, make following changes: + + #GATK="/home/wuk/software/GenomeAnalysisTK.jar" + GATK="/home/wuk/software/gatk-4.0.1.2/gatk-package-4.0.1.2-local.jar" + HG_REF="/home/wuk/Working/gnme_refrnces/Homo_sapiens_assembly19.fasta" + SNPEFF="/home/wuk/software/snpEff/snpEff.jar" + SNPEFF_HG="GRCh37.75" ## SnpEff genome version + +and run with: + + python MACARON -i test_input.vcf --gatk4 + +### demo Folder + +To help verify a successful installation, MACARON includes a small demo data set: + +* *variants_of_interest.vcf* – a test VCF file to check the functionality of MACARON +* *MACARON_output.txt* – The output file generated by running the MACARON +* *sub1.chr22_21349676-21349677.sample02.bam* – a subset of BAM file used as input for MACARON_validate.sh +* *MACARON_validate.txt* – The output file with read count information of concerned pcSNV in sample02 (in this case). +(All files are referenced with hg19) + +`cd` to `demo` folder and run: + + python ../MACARON -i variants_of_interest.vcf + +MACARON_output.txt is the default output file name of MACARON. User can change it with `-o` option. + + python ../MACARON -i variants_of_interest.vcf -o variants_of_interest.txt + +### Advanced Options + +MACARON can be run by invoking paths directly set from the command-line: + +```bash +python ../MACARON -i variants_of_interest.vcf --GATK /home/wuk/software/GenomeAnalysisTK.jar --HG_REF /home/wuk/Working/gnme_refrnces/Homo_sapiens_assembly19.fasta --SNPEFF /home/wuk/software/snpEff/snpEff.jar --SNPEFF_HG GRCh37.75 +``` +* For __GATK >= 4.0__ versions: + +```bash +python ../MACARON -i variants_of_interest.vcf --gatk4 --GATK /home/wuk/software/ --HG_REF /home/wuk/Working/gnme_refrnces/Homo_sapiens_assembly19.fasta --SNPEFF /home/wuk/software/snpEff/snpEff.jar --SNPEFF_HG GRCh37.75 +``` +MACARON can add additional fields, besdies the dafault (see [MACARON Reporting Format](#macaron-reporting-format)) by using `-f` option: + +* `-f CSQ` (if input VCF file is additionally annotated with VEP, the output txt file also has the same complete annotation for each variant record) + +* `-f EFF` (if user wants to output SnpEff annotations in output txt file), or -f ANN (if SnpEff is used without -formatEff option) + +* `-f QUAL,DP,AF,Func.refGene,Gene.refGene,GeneDetail.refGene` (this will keep any other default annotations of input VCF file and of ANNOVAR to output txt file) + +-f can be used multiple times, e.g., + +* `-f CSQ,DP,Func.refGene` +or +* `-f FILTER,EFF,CSQ,AF` + +The order of the fields in the output txt file depends on the order of INFO field headers used in `-f`. + +```bash +python ../MACARON -i variants_of_interest.vcf --gatk4 --GATK /home/wuk/software/ --HG_REF /home/wuk/Working/gnme_refrnces/Homo_sapiens_assembly19.fasta --SNPEFF /home/wuk/software/snpEff/snpEff.jar --SNPEFF_HG GRCh37.75 -f QUAL,FILTER,SIFT_pred +``` +Without `-f` option, `QUAL` field is outputted as default.If user wants to keep `QUAL` along with any other field, `-f` should mentiond `QUAL` in addition to other field headers: `-f QUAL,FILTER,SIFT_pred`. If only `-f SIFT_pred` is used, `QUAL` field is over-written by `SIFT_pred` field. + +# MACARON Reporting Format + +MACARON outputs a table text file with the following format specifications: + +``` +chr22 21349676 rs412470 T A LZTR1 423 T/T T/A T/T 0/0 0/1 0/0 MISSENSE S92T Tct Act ATt I 0 0 +chr22 21349677 rs376419 C T LZTR1 423 C/C C/T C/C 0/0 0/1 0/0 MISSENSE S92F tCt tTt 0 I 0 0 +``` +Field Number | Field Name | Description +--- | --- | --- +1 |CHROM | Chromosome number +2 | POS | Chromosomal position / coordinates of SNV +3 | ID | dbSNP rsID +4 | REF | Reference base +5 | ALT | Alternate base +6 | Gene_Name | Name of a gene in which SnpCluster is located +7 | QUAL | Quality of the ALT base called +8 | [SAMPLE NAME].GT | Genotype of samples as base conventions as well as binary conventions +9 | Protein_coding_EFF | Functional Effect of Variant on protein +10 | AA-Change | Amino acid change by individual SNV +11 | REF-codon | Reference Codon +12 | ALT-codon | Alternate Codon +13 | ALT-codon_merge-2VAR | A new codon formed by the combination of two Alt-codons (pcSNV codon; see [MACARON](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/bty382/4992149?redirectedFrom=fulltext)) +14 | AA-Change-2VAR | Re-annotated amino acid formed by pcSNV codon +15 | ALT-codon_merge-3VAR | A new codon formed by the combination of three Alt-codons +16 | AA-Change-3VAR | Re-annotated amino acid formed by the combination of three Alt-codons + +This default's MACARON output can be changed by using `-f` option. For example, if MACARON run with `-f QUAL,FILTER,SIFT_pred`, the new output looks like: + +Field Number | Field Name | Description +--- | --- | --- +1 |CHROM | Chromosome number +2 | POS | Chromosomal position / coordinates of SNV +3 | ID | dbSNP rsID +4 | REF | Reference base +5 | ALT | Alternate base +6 | Gene_Name | Name of a gene in which SnpCluster is located +7 | QUAL | Quality of the ALT base called +8 | FILTER | Filter (PASS) tag +9 | SIFT_pred | Functional effect prediction of SNV on protien +10 | [SAMPLE NAME].GT | Genotype of samples as base conventions as well as binary conventions +11 | Protein_coding_EFF | Functional Effect of Variant on protein +12 | AA-Change | Amino acid change by individual SNV +13 | REF-codon | Reference Codon +14 | ALT-codon | Alternate Codon +15 | ALT-codon_merge-2VAR | A new codon formed by the combination of two Alt-codons (pcSNV codon; see [MACARON](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/bty382/4992149?redirectedFrom=fulltext)) +16 | AA-Change-2VAR | Re-annotated amino acid formed by pcSNV codon +17 | ALT-codon_merge-3VAR | A new codon formed by the combination of three Alt-codons +18 | AA-Change-3VAR | Re-annotated amino acid formed by the combination of three Alt-codons + +# Validating SNVs Existed on the Same Reads + +**NB: You do not need to run this step if you already used phased VCF file to run MACARON** + +To confirm the existence of multi-SNVs within the same genetic codon, an accessory BASH-shell script [MACARON_validate.sh](MACARON_validate.sh) calculates the read count information of affected bases. This script requires as an input subset of BAM files (should be the same that used to generate the input VCF file) covering 50 bps over each SnpCluster. + +Subset of any BAM file can be generated by using the following command: + +` +samtools view –hb –L sub1.bed sample02.bam > sub1.chr22_21349676-21349677.sample02.bam +` + +In this case, our big BAM file `sample02.bam` (not provided here, obviously!!!) is subsetted as `sub1.chr22_21349676-21349677.sample02.bam` (see [demo](demo) folder) for the position `chr22:21349676`. The naming format of output BAM file should be the same. The `sub1.bed` file has 1 tab-seperated line: + +`chr22 21349676` + +representing the first position of SnpCluster (SNV1 only). + +Once subset BAM file(s) are generated, run MACARON_validate.sh: + +`MACARON_validate.sh sub1.chr22_21349676-21349677.sample02.bam` + +This will generate an output text file (`MACARON_validate.txt`) allowing the user for further analysis. + + sub1 chr22:21349676-21349677 sample02 + 1 AA + 1 T + 11 AT + 14 TC + +See [MACARON-GenMed-LabEx Wiki page](https://github.com/waqasuddinkhan/MACARON-GenMed-LabEx/wiki) for more details, and interpretations of the [demo](demo) data. + +# References + +__1.__ [Van der Auwera G.A., et al. (2013) From FastQ Data to High-Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline, Curr Protoc Bioinformatics, 43:11.10.1-11.10.33](https://currentprotocols.onlinelibrary.wiley.com/doi/abs/10.1002/0471250953.bi1110s43). + +__2.__ [Cingolani, P., et al. (2012) A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3, Fly, 6, 80-92](https://www.tandfonline.com/doi/full/10.4161/fly.19695). + +__3.__ [McLaren, W., et al. (2010) Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor, Bioinformatics, 26, 2069-2070](https://academic.oup.com/bioinformatics/article/26/16/2069/217748). + +__4.__ [Wang, K., Li, M. and Hakonarson, H. (2010) ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data, Nucleic Acids Res, 38, e164](https://academic.oup.com/nar/article/38/16/e164/1749458). + +# Citation + +If you use [MACARON](https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/bty382/4992149?redirectedFrom=fulltext) in your research, please cite: + +*Khan W. et al. MACARON: a python framework to identify and re-annotate multi-base affected codons in whole genome/exome sequence data, Bioinformatics 2018* + +*CONTACT: david-alexandre.tregouet@inserm.fr; waqasnayab@gmail.com* + +*VERSION: 0.7* +*VERSION DATE: September 5, 2018*
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/_config.yml Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,15 @@ +plugins: + - jekyll-seo-tag + +title: macaron +username: waqasuddinkhan +url: https://github.com/waqasuddinkhan/MACARON-GenMed-LabEx + +webmaster_verifications: + google: 1234 + bing: 1234 + alexa: 1234 + yandex: 1234 + baidu: 1234 + +theme: jekyll-theme-cayman
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/demo/MACARON_output.txt Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,5 @@ +CHROM POS ID REF ALT Gene_Name QUAL sample01.GT sample02.GT sample03.GT sample01.GT sample02.GT sample03.GT Protein_coding_Gene_Name AA-Change REF-codon ALT-codon ALT-codon_merge-2VAR AA-Change-2VAR ALT-codon_merge-3VAR AA-Change-3VAR +chr22 21349676 rs412470 T A LZTR1 423.0 T/T T/A T/T 0/0 0/1 0/0 MISSENSE S92T Tct Act ATt I . . +chr22 21349677 rs376419 C T LZTR1 423.0 C/C C/T C/C 0/0 0/1 0/0 MISSENSE S92F tCt tTt . I . . +chr22 23247169 rs527511481 T G IGLJ3 719.0 T/T T/G T/T 0/0 0/1 0/0 MISSENSE W39G Tgg Ggg GTg V . . +chr22 23247170 rs540954398 G T IGLJ3 716.0 G/G G/T G/G 0/0 0/1 0/0 MISSENSE W39L tGg tTg . V . .
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/demo/MACARON_validate.txt Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,5 @@ +sub1 chr22:21349676-21349677 sample02 + 1 AA + 1 T + 11 AT + 14 TC
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/MACARON-GenMed-LabEx/demo/variants_of_interest.vcf Wed Sep 12 08:45:03 2018 -0400 @@ -0,0 +1,395 @@ +##fileformat=VCFv4.2 +##ALT=<ID=NON_REF,Description="Represents any possible alternative allele at this location"> +##FILTER=<ID=LowQual,Description="Low quality"> +##FILTER=<ID=VQSRTrancheINDEL99.00to99.90,Description="Truth sensitivity tranche level for INDEL model at VQS Lod: -16.0255 <= x < -0.8001"> +##FILTER=<ID=VQSRTrancheINDEL99.90to100.00+,Description="Truth sensitivity tranche level for INDEL model at VQS Lod < -37813.1681"> +##FILTER=<ID=VQSRTrancheINDEL99.90to100.00,Description="Truth sensitivity tranche level for INDEL model at VQS Lod: -37813.1681 <= x < -16.0255"> +##FILTER=<ID=VQSRTrancheSNP99.90to100.00+,Description="Truth sensitivity tranche level for SNP model at VQS Lod < -123623.5614"> +##FILTER=<ID=VQSRTrancheSNP99.90to100.00,Description="Truth sensitivity tranche level for SNP model at VQS Lod: -123623.5614 <= x < -2.5203"> +##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Allelic depths for the ref and alt alleles in the order listed"> +##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Approximate read depth (reads with MQ=255 or with bad mates are filtered)"> +##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality"> +##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype"> +##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum DP observed within the GVCF block"> +##FORMAT=<ID=PGT,Number=1,Type=String,Description="Physical phasing haplotype information, describing how the alternate alleles are phased in relation to one another"> +##FORMAT=<ID=PID,Number=1,Type=String,Description="Physical phasing ID information, where each unique ID within a given sample (but not across samples) connects records within a phasing group"> +##FORMAT=<ID=PL,Number=G,Type=Integer,Description="Normalized, Phred-scaled likelihoods for genotypes as defined in the VCF specification"> +##FORMAT=<ID=RGQ,Number=1,Type=Integer,Description="Unconditional reference genotype confidence, encoded as a phred quality -10*log10 p(genotype call is wrong)"> +##FORMAT=<ID=SB,Number=4,Type=Integer,Description="Per-sample component statistics which comprise the Fisher's Exact Test to detect strand bias."> +##GVCFBlock0-1=minGQ=0(inclusive),maxGQ=1(exclusive) +##GVCFBlock1-2=minGQ=1(inclusive),maxGQ=2(exclusive) +##GVCFBlock10-11=minGQ=10(inclusive),maxGQ=11(exclusive) +##GVCFBlock11-12=minGQ=11(inclusive),maxGQ=12(exclusive) +##GVCFBlock12-13=minGQ=12(inclusive),maxGQ=13(exclusive) +##GVCFBlock13-14=minGQ=13(inclusive),maxGQ=14(exclusive) +##GVCFBlock14-15=minGQ=14(inclusive),maxGQ=15(exclusive) +##GVCFBlock15-16=minGQ=15(inclusive),maxGQ=16(exclusive) +##GVCFBlock16-17=minGQ=16(inclusive),maxGQ=17(exclusive) +##GVCFBlock17-18=minGQ=17(inclusive),maxGQ=18(exclusive) +##GVCFBlock18-19=minGQ=18(inclusive),maxGQ=19(exclusive) +##GVCFBlock19-20=minGQ=19(inclusive),maxGQ=20(exclusive) +##GVCFBlock2-3=minGQ=2(inclusive),maxGQ=3(exclusive) +##GVCFBlock20-21=minGQ=20(inclusive),maxGQ=21(exclusive) +##GVCFBlock21-22=minGQ=21(inclusive),maxGQ=22(exclusive) +##GVCFBlock22-23=minGQ=22(inclusive),maxGQ=23(exclusive) +##GVCFBlock23-24=minGQ=23(inclusive),maxGQ=24(exclusive) +##GVCFBlock24-25=minGQ=24(inclusive),maxGQ=25(exclusive) +##GVCFBlock25-26=minGQ=25(inclusive),maxGQ=26(exclusive) +##GVCFBlock26-27=minGQ=26(inclusive),maxGQ=27(exclusive) +##GVCFBlock27-28=minGQ=27(inclusive),maxGQ=28(exclusive) +##GVCFBlock28-29=minGQ=28(inclusive),maxGQ=29(exclusive) +##GVCFBlock29-30=minGQ=29(inclusive),maxGQ=30(exclusive) +##GVCFBlock3-4=minGQ=3(inclusive),maxGQ=4(exclusive) +##GVCFBlock30-31=minGQ=30(inclusive),maxGQ=31(exclusive) +##GVCFBlock31-32=minGQ=31(inclusive),maxGQ=32(exclusive) +##GVCFBlock32-33=minGQ=32(inclusive),maxGQ=33(exclusive) +##GVCFBlock33-34=minGQ=33(inclusive),maxGQ=34(exclusive) +##GVCFBlock34-35=minGQ=34(inclusive),maxGQ=35(exclusive) +##GVCFBlock35-36=minGQ=35(inclusive),maxGQ=36(exclusive) +##GVCFBlock36-37=minGQ=36(inclusive),maxGQ=37(exclusive) +##GVCFBlock37-38=minGQ=37(inclusive),maxGQ=38(exclusive) +##GVCFBlock38-39=minGQ=38(inclusive),maxGQ=39(exclusive) +##GVCFBlock39-40=minGQ=39(inclusive),maxGQ=40(exclusive) +##GVCFBlock4-5=minGQ=4(inclusive),maxGQ=5(exclusive) +##GVCFBlock40-41=minGQ=40(inclusive),maxGQ=41(exclusive) +##GVCFBlock41-42=minGQ=41(inclusive),maxGQ=42(exclusive) +##GVCFBlock42-43=minGQ=42(inclusive),maxGQ=43(exclusive) +##GVCFBlock43-44=minGQ=43(inclusive),maxGQ=44(exclusive) +##GVCFBlock44-45=minGQ=44(inclusive),maxGQ=45(exclusive) +##GVCFBlock45-46=minGQ=45(inclusive),maxGQ=46(exclusive) +##GVCFBlock46-47=minGQ=46(inclusive),maxGQ=47(exclusive) +##GVCFBlock47-48=minGQ=47(inclusive),maxGQ=48(exclusive) +##GVCFBlock48-49=minGQ=48(inclusive),maxGQ=49(exclusive) +##GVCFBlock49-50=minGQ=49(inclusive),maxGQ=50(exclusive) +##GVCFBlock5-6=minGQ=5(inclusive),maxGQ=6(exclusive) +##GVCFBlock50-51=minGQ=50(inclusive),maxGQ=51(exclusive) +##GVCFBlock51-52=minGQ=51(inclusive),maxGQ=52(exclusive) +##GVCFBlock52-53=minGQ=52(inclusive),maxGQ=53(exclusive) +##GVCFBlock53-54=minGQ=53(inclusive),maxGQ=54(exclusive) +##GVCFBlock54-55=minGQ=54(inclusive),maxGQ=55(exclusive) +##GVCFBlock55-56=minGQ=55(inclusive),maxGQ=56(exclusive) +##GVCFBlock56-57=minGQ=56(inclusive),maxGQ=57(exclusive) +##GVCFBlock57-58=minGQ=57(inclusive),maxGQ=58(exclusive) +##GVCFBlock58-59=minGQ=58(inclusive),maxGQ=59(exclusive) +##GVCFBlock59-60=minGQ=59(inclusive),maxGQ=60(exclusive) +##GVCFBlock6-7=minGQ=6(inclusive),maxGQ=7(exclusive) +##GVCFBlock60-70=minGQ=60(inclusive),maxGQ=70(exclusive) +##GVCFBlock7-8=minGQ=7(inclusive),maxGQ=8(exclusive) +##GVCFBlock70-80=minGQ=70(inclusive),maxGQ=80(exclusive) +##GVCFBlock8-9=minGQ=8(inclusive),maxGQ=9(exclusive) +##GVCFBlock80-90=minGQ=80(inclusive),maxGQ=90(exclusive) +##GVCFBlock9-10=minGQ=9(inclusive),maxGQ=10(exclusive) +##GVCFBlock90-99=minGQ=90(inclusive),maxGQ=99(exclusive) +##GVCFBlock99-2147483647=minGQ=99(inclusive),maxGQ=2147483647(exclusive) +##INFO=<ID=AC,Number=A,Type=Integer,Description="Allele count in genotypes, for each ALT allele, in the same order as listed"> +##INFO=<ID=AF,Number=A,Type=Float,Description="Allele Frequency, for each ALT allele, in the same order as listed"> +##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes"> +##INFO=<ID=BaseQRankSum,Number=1,Type=Float,Description="Z-score from Wilcoxon rank sum test of Alt Vs. Ref base qualities"> +##INFO=<ID=ClippingRankSum,Number=1,Type=Float,Description="Z-score From Wilcoxon rank sum test of Alt vs. Ref number of hard clipped bases"> +##INFO=<ID=DB,Number=0,Type=Flag,Description="dbSNP Membership"> +##INFO=<ID=DP,Number=1,Type=Integer,Description="Approximate read depth; some reads may have been filtered"> +##INFO=<ID=DS,Number=0,Type=Flag,Description="Were any of the samples downsampled?"> +##INFO=<ID=END,Number=1,Type=Integer,Description="Stop position of the interval"> +##INFO=<ID=ExcessHet,Number=1,Type=Float,Description="Phred-scaled p-value for exact test of excess heterozygosity"> +##INFO=<ID=FS,Number=1,Type=Float,Description="Phred-scaled p-value using Fisher's exact test to detect strand bias"> +##INFO=<ID=HaplotypeScore,Number=1,Type=Float,Description="Consistency of the site with at most two segregating haplotypes"> +##INFO=<ID=InbreedingCoeff,Number=1,Type=Float,Description="Inbreeding coefficient as estimated from the genotype likelihoods per-sample when compared against the Hardy-Weinberg expectation"> +##INFO=<ID=MLEAC,Number=A,Type=Integer,Description="Maximum likelihood expectation (MLE) for the allele counts (not necessarily the same as the AC), for each ALT allele, in the same order as listed"> +##INFO=<ID=MLEAF,Number=A,Type=Float,Description="Maximum likelihood expectation (MLE) for the allele frequency (not necessarily the same as the AF), for each ALT allele, in the same order as listed"> +##INFO=<ID=MQ,Number=1,Type=Float,Description="RMS Mapping Quality"> +##INFO=<ID=MQRankSum,Number=1,Type=Float,Description="Z-score From Wilcoxon rank sum test of Alt vs. Ref read mapping qualities"> +##INFO=<ID=NEGATIVE_TRAIN_SITE,Number=0,Type=Flag,Description="This variant was used to build the negative training set of bad variants"> +##INFO=<ID=POSITIVE_TRAIN_SITE,Number=0,Type=Flag,Description="This variant was used to build the positive training set of good variants"> +##INFO=<ID=QD,Number=1,Type=Float,Description="Variant Confidence/Quality by Depth"> +##INFO=<ID=RAW_MQ,Number=1,Type=Float,Description="Raw data for RMS Mapping Quality"> +##INFO=<ID=ReadPosRankSum,Number=1,Type=Float,Description="Z-score from Wilcoxon rank sum test of Alt vs. Ref read position bias"> +##INFO=<ID=SOR,Number=1,Type=Float,Description="Symmetric Odds Ratio of 2x2 contingency table to detect strand bias"> +##INFO=<ID=VQSLOD,Number=1,Type=Float,Description="Log odds of being a true variant versus being false under the trained gaussian mixture model"> +##INFO=<ID=culprit,Number=1,Type=String,Description="The annotation which was the worst performing in the Gaussian mixture model, likely the reason why the variant was filtered out"> +##contig=<ID=chr1,length=249250621> +##contig=<ID=chr2,length=243199373> +##contig=<ID=chr3,length=198022430> +##contig=<ID=chr4,length=191154276> +##contig=<ID=chr5,length=180915260> +##contig=<ID=chr6,length=171115067> +##contig=<ID=chr7,length=159138663> +##contig=<ID=chr8,length=146364022> +##contig=<ID=chr9,length=141213431> +##contig=<ID=chr10,length=135534747> +##contig=<ID=chr11,length=135006516> +##contig=<ID=chr12,length=133851895> +##contig=<ID=chr13,length=115169878> +##contig=<ID=chr14,length=107349540> +##contig=<ID=chr15,length=102531392> +##contig=<ID=chr16,length=90354753> +##contig=<ID=chr17,length=81195210> +##contig=<ID=chr18,length=78077248> +##contig=<ID=chr19,length=59128983> +##contig=<ID=chr20,length=63025520> +##contig=<ID=chr21,length=48129895> +##contig=<ID=chr22,length=51304566> +##contig=<ID=chrX,length=155270560> +##contig=<ID=chrY,length=59373566> +##contig=<ID=chrMT,length=16569> +##contig=<ID=chrGL000207.1,length=4262> +##contig=<ID=chrGL000226.1,length=15008> +##contig=<ID=chrGL000229.1,length=19913> +##contig=<ID=chrGL000231.1,length=27386> +##contig=<ID=chrGL000210.1,length=27682> +##contig=<ID=chrGL000239.1,length=33824> +##contig=<ID=chrGL000235.1,length=34474> +##contig=<ID=chrGL000201.1,length=36148> +##contig=<ID=chrGL000247.1,length=36422> +##contig=<ID=chrGL000245.1,length=36651> +##contig=<ID=chrGL000197.1,length=37175> +##contig=<ID=chrGL000203.1,length=37498> +##contig=<ID=chrGL000246.1,length=38154> +##contig=<ID=chrGL000249.1,length=38502> +##contig=<ID=chrGL000196.1,length=38914> +##contig=<ID=chrGL000248.1,length=39786> +##contig=<ID=chrGL000244.1,length=39929> +##contig=<ID=chrGL000238.1,length=39939> +##contig=<ID=chrGL000202.1,length=40103> +##contig=<ID=chrGL000234.1,length=40531> +##contig=<ID=chrGL000232.1,length=40652> +##contig=<ID=chrGL000206.1,length=41001> +##contig=<ID=chrGL000240.1,length=41933> +##contig=<ID=chrGL000236.1,length=41934> +##contig=<ID=chrGL000241.1,length=42152> +##contig=<ID=chrGL000243.1,length=43341> +##contig=<ID=chrGL000242.1,length=43523> +##contig=<ID=chrGL000230.1,length=43691> +##contig=<ID=chrGL000237.1,length=45867> +##contig=<ID=chrGL000233.1,length=45941> +##contig=<ID=chrGL000204.1,length=81310> +##contig=<ID=chrGL000198.1,length=90085> +##contig=<ID=chrGL000208.1,length=92689> +##contig=<ID=chrGL000191.1,length=106433> +##contig=<ID=chrGL000227.1,length=128374> +##contig=<ID=chrGL000228.1,length=129120> +##contig=<ID=chrGL000214.1,length=137718> +##contig=<ID=chrGL000221.1,length=155397> +##contig=<ID=chrGL000209.1,length=159169> +##contig=<ID=chrGL000218.1,length=161147> +##contig=<ID=chrGL000220.1,length=161802> +##contig=<ID=chrGL000213.1,length=164239> +##contig=<ID=chrGL000211.1,length=166566> +##contig=<ID=chrGL000199.1,length=169874> +##contig=<ID=chrGL000217.1,length=172149> +##contig=<ID=chrGL000216.1,length=172294> +##contig=<ID=chrGL000215.1,length=172545> +##contig=<ID=chrGL000205.1,length=174588> +##contig=<ID=chrGL000219.1,length=179198> +##contig=<ID=chrGL000224.1,length=179693> +##contig=<ID=chrGL000223.1,length=180455> +##contig=<ID=chrGL000195.1,length=182896> +##contig=<ID=chrGL000212.1,length=186858> +##contig=<ID=chrGL000222.1,length=186861> +##contig=<ID=chrGL000200.1,length=187035> +##contig=<ID=chrGL000193.1,length=189789> +##contig=<ID=chrGL000194.1,length=191469> +##contig=<ID=chrGL000225.1,length=211173> +##contig=<ID=chrGL000192.1,length=547496> +##contig=<ID=chrNC_007605,length=171823> +##reference=file:///home/wuk/Working/gnme_refrnces/Homo_sapiens_assembly19.fasta +##source=SelectVariants +##SnpEffVersion="4.3m (build 2017-05-05 18:41), by Pablo Cingolani" +##INFO=<ID=EFF,Number=.,Type=String,Description="Predicted effects for this variant.Format: 'Effect ( Effect_Impact | Functional_Class | Codon_Change | Amino_Acid_Change| Amino_Acid_length | Gene_Name | Transcript_BioType | Gene_Coding | Transcript_ID | Exon_Rank | Genotype [ | ERRORS | WARNINGS ] )' "> +##INFO=<ID=LOF,Number=.,Type=String,Description="Predicted loss of function effects for this variant. Format: 'Gene_Name | Gene_ID | Number_of_transcripts_in_gene | Percent_of_transcripts_affected'"> +##INFO=<ID=NMD,Number=.,Type=String,Description="Predicted nonsense mediated decay effects for this variant. Format: 'Gene_Name | Gene_ID | Number_of_transcripts_in_gene | Percent_of_transcripts_affected'"> +##INFO=<ID=ANNOVAR_DATE,Number=1,Type=String,Description="Flag the start of ANNOVAR annotation for one alternative allele"> +##INFO=<ID=Func.refGene,Number=.,Type=String,Description="Func.refGene annotation provided by ANNOVAR"> +##INFO=<ID=Gene.refGene,Number=.,Type=String,Description="Gene.refGene annotation provided by ANNOVAR"> +##INFO=<ID=GeneDetail.refGene,Number=.,Type=String,Description="GeneDetail.refGene annotation provided by ANNOVAR"> +##INFO=<ID=ExonicFunc.refGene,Number=.,Type=String,Description="ExonicFunc.refGene annotation provided by ANNOVAR"> +##INFO=<ID=AAChange.refGene,Number=.,Type=String,Description="AAChange.refGene annotation provided by ANNOVAR"> +##INFO=<ID=SIFT_score,Number=.,Type=String,Description="SIFT_score annotation provided by ANNOVAR"> +##INFO=<ID=SIFT_pred,Number=.,Type=String,Description="SIFT_pred annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HDIV_score,Number=.,Type=String,Description="Polyphen2_HDIV_score annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HDIV_pred,Number=.,Type=String,Description="Polyphen2_HDIV_pred annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HVAR_score,Number=.,Type=String,Description="Polyphen2_HVAR_score annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HVAR_pred,Number=.,Type=String,Description="Polyphen2_HVAR_pred annotation provided by ANNOVAR"> +##INFO=<ID=LRT_score,Number=.,Type=String,Description="LRT_score annotation provided by ANNOVAR"> +##INFO=<ID=LRT_pred,Number=.,Type=String,Description="LRT_pred annotation provided by ANNOVAR"> +##INFO=<ID=MutationTaster_score,Number=.,Type=String,Description="MutationTaster_score annotation provided by ANNOVAR"> +##INFO=<ID=MutationTaster_pred,Number=.,Type=String,Description="MutationTaster_pred annotation provided by ANNOVAR"> +##INFO=<ID=MutationAssessor_score,Number=.,Type=String,Description="MutationAssessor_score annotation provided by ANNOVAR"> +##INFO=<ID=MutationAssessor_pred,Number=.,Type=String,Description="MutationAssessor_pred annotation provided by ANNOVAR"> +##INFO=<ID=FATHMM_score,Number=.,Type=String,Description="FATHMM_score annotation provided by ANNOVAR"> +##INFO=<ID=FATHMM_pred,Number=.,Type=String,Description="FATHMM_pred annotation provided by ANNOVAR"> +##INFO=<ID=RadialSVM_score,Number=.,Type=String,Description="RadialSVM_score annotation provided by ANNOVAR"> +##INFO=<ID=RadialSVM_pred,Number=.,Type=String,Description="RadialSVM_pred annotation provided by ANNOVAR"> +##INFO=<ID=LR_score,Number=.,Type=String,Description="LR_score annotation provided by ANNOVAR"> +##INFO=<ID=LR_pred,Number=.,Type=String,Description="LR_pred annotation provided by ANNOVAR"> +##INFO=<ID=VEST3_score,Number=.,Type=String,Description="VEST3_score annotation provided by ANNOVAR"> +##INFO=<ID=CADD_raw,Number=.,Type=String,Description="CADD_raw annotation provided by ANNOVAR"> +##INFO=<ID=CADD_phred,Number=.,Type=String,Description="CADD_phred annotation provided by ANNOVAR"> +##INFO=<ID=GERP++_RS,Number=.,Type=String,Description="GERP++_RS annotation provided by ANNOVAR"> +##INFO=<ID=phyloP46way_placental,Number=.,Type=String,Description="phyloP46way_placental annotation provided by ANNOVAR"> +##INFO=<ID=phyloP100way_vertebrate,Number=.,Type=String,Description="phyloP100way_vertebrate annotation provided by ANNOVAR"> +##INFO=<ID=SiPhy_29way_logOdds,Number=.,Type=String,Description="SiPhy_29way_logOdds annotation provided by ANNOVAR"> +##INFO=<ID=SIFT_score,Number=.,Type=String,Description="SIFT_score annotation provided by ANNOVAR"> +##INFO=<ID=SIFT_converted_rankscore,Number=.,Type=String,Description="SIFT_converted_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=SIFT_pred,Number=.,Type=String,Description="SIFT_pred annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HDIV_score,Number=.,Type=String,Description="Polyphen2_HDIV_score annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HDIV_rankscore,Number=.,Type=String,Description="Polyphen2_HDIV_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HDIV_pred,Number=.,Type=String,Description="Polyphen2_HDIV_pred annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HVAR_score,Number=.,Type=String,Description="Polyphen2_HVAR_score annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HVAR_rankscore,Number=.,Type=String,Description="Polyphen2_HVAR_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=Polyphen2_HVAR_pred,Number=.,Type=String,Description="Polyphen2_HVAR_pred annotation provided by ANNOVAR"> +##INFO=<ID=LRT_score,Number=.,Type=String,Description="LRT_score annotation provided by ANNOVAR"> +##INFO=<ID=LRT_converted_rankscore,Number=.,Type=String,Description="LRT_converted_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=LRT_pred,Number=.,Type=String,Description="LRT_pred annotation provided by ANNOVAR"> +##INFO=<ID=MutationTaster_score,Number=.,Type=String,Description="MutationTaster_score annotation provided by ANNOVAR"> +##INFO=<ID=MutationTaster_converted_rankscore,Number=.,Type=String,Description="MutationTaster_converted_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=MutationTaster_pred,Number=.,Type=String,Description="MutationTaster_pred annotation provided by ANNOVAR"> +##INFO=<ID=MutationAssessor_score,Number=.,Type=String,Description="MutationAssessor_score annotation provided by ANNOVAR"> +##INFO=<ID=MutationAssessor_score_rankscore,Number=.,Type=String,Description="MutationAssessor_score_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=MutationAssessor_pred,Number=.,Type=String,Description="MutationAssessor_pred annotation provided by ANNOVAR"> +##INFO=<ID=FATHMM_score,Number=.,Type=String,Description="FATHMM_score annotation provided by ANNOVAR"> +##INFO=<ID=FATHMM_converted_rankscore,Number=.,Type=String,Description="FATHMM_converted_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=FATHMM_pred,Number=.,Type=String,Description="FATHMM_pred annotation provided by ANNOVAR"> +##INFO=<ID=PROVEAN_score,Number=.,Type=String,Description="PROVEAN_score annotation provided by ANNOVAR"> +##INFO=<ID=PROVEAN_converted_rankscore,Number=.,Type=String,Description="PROVEAN_converted_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=PROVEAN_pred,Number=.,Type=String,Description="PROVEAN_pred annotation provided by ANNOVAR"> +##INFO=<ID=VEST3_score,Number=.,Type=String,Description="VEST3_score annotation provided by ANNOVAR"> +##INFO=<ID=VEST3_rankscore,Number=.,Type=String,Description="VEST3_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=MetaSVM_score,Number=.,Type=String,Description="MetaSVM_score annotation provided by ANNOVAR"> +##INFO=<ID=MetaSVM_rankscore,Number=.,Type=String,Description="MetaSVM_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=MetaSVM_pred,Number=.,Type=String,Description="MetaSVM_pred annotation provided by ANNOVAR"> +##INFO=<ID=MetaLR_score,Number=.,Type=String,Description="MetaLR_score annotation provided by ANNOVAR"> +##INFO=<ID=MetaLR_rankscore,Number=.,Type=String,Description="MetaLR_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=MetaLR_pred,Number=.,Type=String,Description="MetaLR_pred annotation provided by ANNOVAR"> +##INFO=<ID=M-CAP_score,Number=.,Type=String,Description="M-CAP_score annotation provided by ANNOVAR"> +##INFO=<ID=M-CAP_rankscore,Number=.,Type=String,Description="M-CAP_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=M-CAP_pred,Number=.,Type=String,Description="M-CAP_pred annotation provided by ANNOVAR"> +##INFO=<ID=CADD_raw,Number=.,Type=String,Description="CADD_raw annotation provided by ANNOVAR"> +##INFO=<ID=CADD_raw_rankscore,Number=.,Type=String,Description="CADD_raw_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=CADD_phred,Number=.,Type=String,Description="CADD_phred annotation provided by ANNOVAR"> +##INFO=<ID=DANN_score,Number=.,Type=String,Description="DANN_score annotation provided by ANNOVAR"> +##INFO=<ID=DANN_rankscore,Number=.,Type=String,Description="DANN_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=fathmm-MKL_coding_score,Number=.,Type=String,Description="fathmm-MKL_coding_score annotation provided by ANNOVAR"> +##INFO=<ID=fathmm-MKL_coding_rankscore,Number=.,Type=String,Description="fathmm-MKL_coding_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=fathmm-MKL_coding_pred,Number=.,Type=String,Description="fathmm-MKL_coding_pred annotation provided by ANNOVAR"> +##INFO=<ID=Eigen_coding_or_noncoding,Number=.,Type=String,Description="Eigen_coding_or_noncoding annotation provided by ANNOVAR"> +##INFO=<ID=Eigen-raw,Number=.,Type=String,Description="Eigen-raw annotation provided by ANNOVAR"> +##INFO=<ID=Eigen-PC-raw,Number=.,Type=String,Description="Eigen-PC-raw annotation provided by ANNOVAR"> +##INFO=<ID=GenoCanyon_score,Number=.,Type=String,Description="GenoCanyon_score annotation provided by ANNOVAR"> +##INFO=<ID=GenoCanyon_score_rankscore,Number=.,Type=String,Description="GenoCanyon_score_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=integrated_fitCons_score,Number=.,Type=String,Description="integrated_fitCons_score annotation provided by ANNOVAR"> +##INFO=<ID=integrated_fitCons_score_rankscore,Number=.,Type=String,Description="integrated_fitCons_score_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=integrated_confidence_value,Number=.,Type=String,Description="integrated_confidence_value annotation provided by ANNOVAR"> +##INFO=<ID=GERP++_RS,Number=.,Type=String,Description="GERP++_RS annotation provided by ANNOVAR"> +##INFO=<ID=GERP++_RS_rankscore,Number=.,Type=String,Description="GERP++_RS_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=phyloP100way_vertebrate,Number=.,Type=String,Description="phyloP100way_vertebrate annotation provided by ANNOVAR"> +##INFO=<ID=phyloP100way_vertebrate_rankscore,Number=.,Type=String,Description="phyloP100way_vertebrate_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=phyloP20way_mammalian,Number=.,Type=String,Description="phyloP20way_mammalian annotation provided by ANNOVAR"> +##INFO=<ID=phyloP20way_mammalian_rankscore,Number=.,Type=String,Description="phyloP20way_mammalian_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=phastCons100way_vertebrate,Number=.,Type=String,Description="phastCons100way_vertebrate annotation provided by ANNOVAR"> +##INFO=<ID=phastCons100way_vertebrate_rankscore,Number=.,Type=String,Description="phastCons100way_vertebrate_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=phastCons20way_mammalian,Number=.,Type=String,Description="phastCons20way_mammalian annotation provided by ANNOVAR"> +##INFO=<ID=phastCons20way_mammalian_rankscore,Number=.,Type=String,Description="phastCons20way_mammalian_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=SiPhy_29way_logOdds,Number=.,Type=String,Description="SiPhy_29way_logOdds annotation provided by ANNOVAR"> +##INFO=<ID=SiPhy_29way_logOdds_rankscore,Number=.,Type=String,Description="SiPhy_29way_logOdds_rankscore annotation provided by ANNOVAR"> +##INFO=<ID=Interpro_domain,Number=.,Type=String,Description="Interpro_domain annotation provided by ANNOVAR"> +##INFO=<ID=GTEx_V6_gene,Number=.,Type=String,Description="GTEx_V6_gene annotation provided by ANNOVAR"> +##INFO=<ID=GTEx_V6_tissue,Number=.,Type=String,Description="GTEx_V6_tissue annotation provided by ANNOVAR"> +##INFO=<ID=dbscSNV_ADA_SCORE,Number=.,Type=String,Description="dbscSNV_ADA_SCORE annotation provided by ANNOVAR"> +##INFO=<ID=dbscSNV_RF_SCORE,Number=.,Type=String,Description="dbscSNV_RF_SCORE annotation provided by ANNOVAR"> +##INFO=<ID=InterVar(automated),Number=.,Type=String,Description="InterVar(automated) annotation provided by ANNOVAR"> +##INFO=<ID=PVS1,Number=.,Type=String,Description="PVS1 annotation provided by ANNOVAR"> +##INFO=<ID=PS1,Number=.,Type=String,Description="PS1 annotation provided by ANNOVAR"> +##INFO=<ID=PS2,Number=.,Type=String,Description="PS2 annotation provided by ANNOVAR"> +##INFO=<ID=PS3,Number=.,Type=String,Description="PS3 annotation provided by ANNOVAR"> +##INFO=<ID=PS4,Number=.,Type=String,Description="PS4 annotation provided by ANNOVAR"> +##INFO=<ID=PM1,Number=.,Type=String,Description="PM1 annotation provided by ANNOVAR"> +##INFO=<ID=PM2,Number=.,Type=String,Description="PM2 annotation provided by ANNOVAR"> +##INFO=<ID=PM3,Number=.,Type=String,Description="PM3 annotation provided by ANNOVAR"> +##INFO=<ID=PM4,Number=.,Type=String,Description="PM4 annotation provided by ANNOVAR"> +##INFO=<ID=PM5,Number=.,Type=String,Description="PM5 annotation provided by ANNOVAR"> +##INFO=<ID=PM6,Number=.,Type=String,Description="PM6 annotation provided by ANNOVAR"> +##INFO=<ID=PP1,Number=.,Type=String,Description="PP1 annotation provided by ANNOVAR"> +##INFO=<ID=PP2,Number=.,Type=String,Description="PP2 annotation provided by ANNOVAR"> +##INFO=<ID=PP3,Number=.,Type=String,Description="PP3 annotation provided by ANNOVAR"> +##INFO=<ID=PP4,Number=.,Type=String,Description="PP4 annotation provided by ANNOVAR"> +##INFO=<ID=PP5,Number=.,Type=String,Description="PP5 annotation provided by ANNOVAR"> +##INFO=<ID=BA1,Number=.,Type=String,Description="BA1 annotation provided by ANNOVAR"> +##INFO=<ID=BS1,Number=.,Type=String,Description="BS1 annotation provided by ANNOVAR"> +##INFO=<ID=BS2,Number=.,Type=String,Description="BS2 annotation provided by ANNOVAR"> +##INFO=<ID=BS3,Number=.,Type=String,Description="BS3 annotation provided by ANNOVAR"> +##INFO=<ID=BS4,Number=.,Type=String,Description="BS4 annotation provided by ANNOVAR"> +##INFO=<ID=BP1,Number=.,Type=String,Description="BP1 annotation provided by ANNOVAR"> +##INFO=<ID=BP2,Number=.,Type=String,Description="BP2 annotation provided by ANNOVAR"> +##INFO=<ID=BP3,Number=.,Type=String,Description="BP3 annotation provided by ANNOVAR"> +##INFO=<ID=BP4,Number=.,Type=String,Description="BP4 annotation provided by ANNOVAR"> +##INFO=<ID=BP5,Number=.,Type=String,Description="BP5 annotation provided by ANNOVAR"> +##INFO=<ID=BP6,Number=.,Type=String,Description="BP6 annotation provided by ANNOVAR"> +##INFO=<ID=BP7,Number=.,Type=String,Description="BP7 annotation provided by ANNOVAR"> +##INFO=<ID=esp6500siv2_ea,Number=1,Type=Float,Description="esp6500siv2_ea annotation provided by ANNOVAR"> +##INFO=<ID=esp6500siv2_all,Number=1,Type=Float,Description="esp6500siv2_all annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_ALL,Number=.,Type=String,Description="ExAC_ALL annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_AFR,Number=.,Type=String,Description="ExAC_AFR annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_AMR,Number=.,Type=String,Description="ExAC_AMR annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_EAS,Number=.,Type=String,Description="ExAC_EAS annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_FIN,Number=.,Type=String,Description="ExAC_FIN annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_NFE,Number=.,Type=String,Description="ExAC_NFE annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_OTH,Number=.,Type=String,Description="ExAC_OTH annotation provided by ANNOVAR"> +##INFO=<ID=ExAC_SAS,Number=.,Type=String,Description="ExAC_SAS annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_ALL,Number=.,Type=String,Description="gnomAD_exome_ALL annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_AFR,Number=.,Type=String,Description="gnomAD_exome_AFR annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_AMR,Number=.,Type=String,Description="gnomAD_exome_AMR annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_ASJ,Number=.,Type=String,Description="gnomAD_exome_ASJ annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_EAS,Number=.,Type=String,Description="gnomAD_exome_EAS annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_FIN,Number=.,Type=String,Description="gnomAD_exome_FIN annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_NFE,Number=.,Type=String,Description="gnomAD_exome_NFE annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_OTH,Number=.,Type=String,Description="gnomAD_exome_OTH annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_exome_SAS,Number=.,Type=String,Description="gnomAD_exome_SAS annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_ALL,Number=.,Type=String,Description="gnomAD_genome_ALL annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_AFR,Number=.,Type=String,Description="gnomAD_genome_AFR annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_AMR,Number=.,Type=String,Description="gnomAD_genome_AMR annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_ASJ,Number=.,Type=String,Description="gnomAD_genome_ASJ annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_EAS,Number=.,Type=String,Description="gnomAD_genome_EAS annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_FIN,Number=.,Type=String,Description="gnomAD_genome_FIN annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_NFE,Number=.,Type=String,Description="gnomAD_genome_NFE annotation provided by ANNOVAR"> +##INFO=<ID=gnomAD_genome_OTH,Number=.,Type=String,Description="gnomAD_genome_OTH annotation provided by ANNOVAR"> +##INFO=<ID=1000g2015aug_all,Number=1,Type=Float,Description="1000g2015aug_all annotation provided by ANNOVAR"> +##INFO=<ID=MCAP,Number=.,Type=String,Description="MCAP annotation provided by ANNOVAR"> +##INFO=<ID=REVEL,Number=.,Type=String,Description="REVEL annotation provided by ANNOVAR"> +##INFO=<ID=GWAVA_region_score,Number=.,Type=String,Description="GWAVA_region_score annotation provided by ANNOVAR"> +##INFO=<ID=GWAVA_tss_score,Number=.,Type=String,Description="GWAVA_tss_score annotation provided by ANNOVAR"> +##INFO=<ID=GWAVA_unmatched_score,Number=.,Type=String,Description="GWAVA_unmatched_score annotation provided by ANNOVAR"> +##INFO=<ID=ALLELE_END,Number=0,Type=Flag,Description="Flag the end of ANNOVAR annotation for one alternative allele"> +##INFO=<ID=ANNOVAR_DATE,Number=1,Type=String,Description="Flag the start of ANNOVAR annotation for one alternative allele"> +##INFO=<ID=CADD13_RawScore,Number=.,Type=String,Description="CADD13_RawScore annotation provided by ANNOVAR"> +##INFO=<ID=CADD13_PHRED,Number=.,Type=String,Description="CADD13_PHRED annotation provided by ANNOVAR"> +##INFO=<ID=ALLELE_END,Number=0,Type=Flag,Description="Flag the end of ANNOVAR annotation for one alternative allele"> +##INFO=<ID=DP4,Number=4,Type=Integer,Description="# high-quality ref-forward bases, ref-reverse, alt-forward and alt-reverse bases"> +##INFO=<ID=FQ,Number=1,Type=Float,Description="Phred probability of all samples being the same"> +##INFO=<ID=AF1,Number=1,Type=Float,Description="Max-likelihood estimate of the first ALT allele frequency (assuming HWE)"> +##INFO=<ID=AC1,Number=1,Type=Float,Description="Max-likelihood estimate of the first ALT allele count (no HWE assumption)"> +##INFO=<ID=IS,Number=2,Type=Float,Description="Maximum number of reads supporting an indel and fraction of indel reads"> +##INFO=<ID=G3,Number=3,Type=Float,Description="ML estimate of genotype frequencies"> +##INFO=<ID=HWE,Number=1,Type=Float,Description="Chi^2 based HWE test P-value based on G3"> +##INFO=<ID=CLR,Number=1,Type=Integer,Description="Log ratio of genotype likelihoods with and without the constraint"> +##INFO=<ID=UGT,Number=1,Type=String,Description="The most probable unconstrained genotype configuration in the trio"> +##INFO=<ID=CGT,Number=1,Type=String,Description="The most probable constrained genotype configuration in the trio"> +##INFO=<ID=PV4,Number=4,Type=Float,Description="P-values for strand bias, baseQ bias, mapQ bias and tail distance bias"> +##INFO=<ID=INDEL,Number=0,Type=Flag,Description="Indicates that the variant is an INDEL."> +##INFO=<ID=PC2,Number=2,Type=Integer,Description="Phred probability of the nonRef allele frequency in group1 samples being larger (,smaller) than in group2."> +##INFO=<ID=PCHI2,Number=1,Type=Float,Description="Posterior weighted chi^2 P-value for testing the association between group1 and group2 samples."> +##INFO=<ID=QCHI2,Number=1,Type=Integer,Description="Phred scaled PCHI2."> +##INFO=<ID=PR,Number=1,Type=Integer,Description="# permutations yielding a smaller PCHI2."> +##INFO=<ID=QBD,Number=1,Type=Float,Description="Quality by Depth: QUAL/#reads"> +##INFO=<ID=RPB,Number=1,Type=Float,Description="Read Position Bias"> +##INFO=<ID=MDV,Number=1,Type=Integer,Description="Maximum number of high-quality nonRef reads in samples"> +##INFO=<ID=VDB,Number=1,Type=Float,Description="Variant Distance Bias (v2) for filtering splice-site artefacts in RNA-seq data. Note: this version may be broken."> +##FORMAT=<ID=GL,Number=3,Type=Float,Description="Likelihoods for RR,RA,AA genotypes (R=ref,A=alt)"> +##FORMAT=<ID=DV,Number=1,Type=Integer,Description="# high-quality non-reference bases"> +##FORMAT=<ID=SP,Number=1,Type=Integer,Description="Phred-scaled strand bias P-value"> +#CHROM POS ID REF ALT QUAL FILTER INFO FORMAT sample01 sample02 sample03 +chr22 17565035 rs4819554 G A 3.39e+03 PASS AC=6;AF=1.00;AN=6;DB;DP=96;ExcessHet=3.0103;FS=0.000;MLEAC=6;MLEAF=1.00;MQ=60.00;POSITIVE_TRAIN_SITE;QD=27.46;SOR=1.167;VQSLOD=6.60;culprit=QD;EFF=UPSTREAM(MODIFIER||814||866|IL17RA|protein_coding|CODING|ENST00000319363||A),UPSTREAM(MODIFIER||809|||IL17RA|processed_transcript|CODING|ENST00000477874||A),UPSTREAM(MODIFIER||912|||IL17RA|retained_intron|CODING|ENST00000459971||A),DOWNSTREAM(MODIFIER||2689|||AC006946.17|lincRNA|NON_CODING|ENST00000609791||A),INTERGENIC(MODIFIER||||||||||A);ANNOVAR_DATE=2016-02-01;Func.refGene=upstream;Gene.refGene=IL17RA;GeneDetail.refGene=.;ExonicFunc.refGene=.;AAChange.refGene=.;SIFT_score=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_pred=.;RadialSVM_score=.;RadialSVM_pred=.;LR_score=.;LR_pred=.;VEST3_score=.;CADD_raw=.;CADD_phred=.;GERP++_RS=.;phyloP46way_placental=.;phyloP100way_vertebrate=.;SiPhy_29way_logOdds=.;SIFT_score=.;SIFT_converted_rankscore=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_rankscore=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_rankscore=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_converted_rankscore=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_converted_rankscore=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_score_rankscore=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_converted_rankscore=.;FATHMM_pred=.;PROVEAN_score=.;PROVEAN_converted_rankscore=.;PROVEAN_pred=.;VEST3_score=.;VEST3_rankscore=.;MetaSVM_score=.;MetaSVM_rankscore=.;MetaSVM_pred=.;MetaLR_score=.;MetaLR_rankscore=.;MetaLR_pred=.;M-CAP_score=.;M-CAP_rankscore=.;M-CAP_pred=.;CADD_raw=.;CADD_raw_rankscore=.;CADD_phred=.;DANN_score=.;DANN_rankscore=.;fathmm-MKL_coding_score=.;fathmm-MKL_coding_rankscore=.;fathmm-MKL_coding_pred=.;Eigen_coding_or_noncoding=.;Eigen-raw=.;Eigen-PC-raw=.;GenoCanyon_score=.;GenoCanyon_score_rankscore=.;integrated_fitCons_score=.;integrated_fitCons_score_rankscore=.;integrated_confidence_value=.;GERP++_RS=.;GERP++_RS_rankscore=.;phyloP100way_vertebrate=.;phyloP100way_vertebrate_rankscore=.;phyloP20way_mammalian=.;phyloP20way_mammalian_rankscore=.;phastCons100way_vertebrate=.;phastCons100way_vertebrate_rankscore=.;phastCons20way_mammalian=.;phastCons20way_mammalian_rankscore=.;SiPhy_29way_logOdds=.;SiPhy_29way_logOdds_rankscore=.;Interpro_domain=.;GTEx_V6_gene=.;GTEx_V6_tissue=.;dbscSNV_ADA_SCORE=.;dbscSNV_RF_SCORE=.;InterVar(automated)=.;PVS1=.;PS1=.;PS2=.;PS3=.;PS4=.;PM1=.;PM2=.;PM3=.;PM4=.;PM5=.;PM6=.;PP1=.;PP2=.;PP3=.;PP4=.;PP5=.;BA1=.;BS1=.;BS2=.;BS3=.;BS4=.;BP1=.;BP2=.;BP3=.;BP4=.;BP5=.;BP6=.;BP7=.;esp6500siv2_ea=.;esp6500siv2_all=.;ExAC_ALL=.;ExAC_AFR=.;ExAC_AMR=.;ExAC_EAS=.;ExAC_FIN=.;ExAC_NFE=.;ExAC_OTH=.;ExAC_SAS=.;gnomAD_exome_ALL=.;gnomAD_exome_AFR=.;gnomAD_exome_AMR=.;gnomAD_exome_ASJ=.;gnomAD_exome_EAS=.;gnomAD_exome_FIN=.;gnomAD_exome_NFE=.;gnomAD_exome_OTH=.;gnomAD_exome_SAS=.;gnomAD_genome_ALL=.;gnomAD_genome_AFR=.;gnomAD_genome_AMR=.;gnomAD_genome_ASJ=.;gnomAD_genome_EAS=.;gnomAD_genome_FIN=.;gnomAD_genome_NFE=.;gnomAD_genome_OTH=.;1000g2015aug_all=0.766973;MCAP=.;REVEL=.;GWAVA_region_score=0.35;GWAVA_tss_score=0.57;GWAVA_unmatched_score=182;ALLELE_END;ANNOVAR_DATE=2016-02-01;CADD13_RawScore=0.154414;CADD13_PHRED=4.193;ALLELE_END GT:AD:DP:GQ:PL 1/1:.:40:99:255,120,0 1/1:.:25:75:255,75,0 1/1:.:30:89:255,89,0 +chr22 21349676 rs412470 T A 423 PASS AC=1;AF=0.167;AN=6;BaseQRankSum=-8.270e-01;ClippingRankSum=0.00;DB;DP=92;ExcessHet=3.0103;FS=1.623;MLEAC=1;MLEAF=0.167;MQ=60.00;MQRankSum=0.00;QD=16.93;ReadPosRankSum=0.120;SOR=0.368;VQSLOD=7.61;culprit=MQRankSum;EFF=NON_SYNONYMOUS_CODING(MODERATE|MISSENSE|Tct/Act|S92T|97|LZTR1|nonsense_mediated_decay|CODING|ENST00000415354|4|A),SPLICE_SITE_REGION+EXON(LOW|||||LZTR1|retained_intron|CODING|ENST00000464807|2|A),SYNONYMOUS_CODING(LOW|SILENT|gcT/gcA|A81|110|LZTR1|nonsense_mediated_decay|CODING|ENST00000439171|3|A|WARNING_TRANSCRIPT_NO_START_CODON),UPSTREAM(MODIFIER||401|||LZTR1|retained_intron|CODING|ENST00000498649||A),UPSTREAM(MODIFIER||609||157|LZTR1|protein_coding|CODING|ENST00000415817||A|WARNING_TRANSCRIPT_NO_START_CODON),DOWNSTREAM(MODIFIER||4385||309|THAP7|protein_coding|CODING|ENST00000215742||A),DOWNSTREAM(MODIFIER||3702||117|LZTR1|nonsense_mediated_decay|CODING|ENST00000414985||A),DOWNSTREAM(MODIFIER||3708|||LZTR1|processed_transcript|CODING|ENST00000480895||A),DOWNSTREAM(MODIFIER||2539|||LZTR1|processed_transcript|CODING|ENST00000497716||A),DOWNSTREAM(MODIFIER||2855|||LZTR1|retained_intron|CODING|ENST00000461510||A),DOWNSTREAM(MODIFIER||1087|||LZTR1|retained_intron|CODING|ENST00000492480||A),DOWNSTREAM(MODIFIER||3717|||THAP7|retained_intron|CODING|ENST00000498406||A),DOWNSTREAM(MODIFIER||4386|||THAP7|retained_intron|CODING|ENST00000471073||A),DOWNSTREAM(MODIFIER||4390||309|THAP7|protein_coding|CODING|ENST00000399133||A),DOWNSTREAM(MODIFIER||4415|||THAP7|retained_intron|CODING|ENST00000476667||A),DOWNSTREAM(MODIFIER||4843|||THAP7|retained_intron|CODING|ENST00000466670||A),DOWNSTREAM(MODIFIER||4885|||THAP7|retained_intron|CODING|ENST00000488975||A),INTRON(MODIFIER||||840|LZTR1|protein_coding|CODING|ENST00000215739|16|A),INTRON(MODIFIER|||||LZTR1|processed_transcript|CODING|ENST00000479606|17|A),INTRON(MODIFIER||||821|LZTR1|protein_coding|CODING|ENST00000389355|15|A),INTRON(MODIFIER|||||LZTR1|retained_intron|CODING|ENST00000495142|2|A),INTRON(MODIFIER|||||LZTR1|retained_intron|CODING|ENST00000491432|2|A),INTRON(MODIFIER||||54|LZTR1|nonsense_mediated_decay|CODING|ENST00000452988|1|A|WARNING_TRANSCRIPT_NO_START_CODON),EXON(MODIFIER|||||LZTR1|retained_intron|CODING|ENST00000463909|1|A);ANNOVAR_DATE=2016-02-01;Func.refGene=intronic;Gene.refGene=LZTR1;GeneDetail.refGene=.;ExonicFunc.refGene=.;AAChange.refGene=.;SIFT_score=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_pred=.;RadialSVM_score=.;RadialSVM_pred=.;LR_score=.;LR_pred=.;VEST3_score=.;CADD_raw=.;CADD_phred=.;GERP++_RS=.;phyloP46way_placental=.;phyloP100way_vertebrate=.;SiPhy_29way_logOdds=.;SIFT_score=.;SIFT_converted_rankscore=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_rankscore=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_rankscore=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_converted_rankscore=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_converted_rankscore=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_score_rankscore=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_converted_rankscore=.;FATHMM_pred=.;PROVEAN_score=.;PROVEAN_converted_rankscore=.;PROVEAN_pred=.;VEST3_score=.;VEST3_rankscore=.;MetaSVM_score=.;MetaSVM_rankscore=.;MetaSVM_pred=.;MetaLR_score=.;MetaLR_rankscore=.;MetaLR_pred=.;M-CAP_score=.;M-CAP_rankscore=.;M-CAP_pred=.;CADD_raw=.;CADD_raw_rankscore=.;CADD_phred=.;DANN_score=.;DANN_rankscore=.;fathmm-MKL_coding_score=.;fathmm-MKL_coding_rankscore=.;fathmm-MKL_coding_pred=.;Eigen_coding_or_noncoding=.;Eigen-raw=.;Eigen-PC-raw=.;GenoCanyon_score=.;GenoCanyon_score_rankscore=.;integrated_fitCons_score=.;integrated_fitCons_score_rankscore=.;integrated_confidence_value=.;GERP++_RS=.;GERP++_RS_rankscore=.;phyloP100way_vertebrate=.;phyloP100way_vertebrate_rankscore=.;phyloP20way_mammalian=.;phyloP20way_mammalian_rankscore=.;phastCons100way_vertebrate=.;phastCons100way_vertebrate_rankscore=.;phastCons20way_mammalian=.;phastCons20way_mammalian_rankscore=.;SiPhy_29way_logOdds=.;SiPhy_29way_logOdds_rankscore=.;Interpro_domain=.;GTEx_V6_gene=.;GTEx_V6_tissue=.;dbscSNV_ADA_SCORE=.;dbscSNV_RF_SCORE=.;InterVar(automated)=.;PVS1=.;PS1=.;PS2=.;PS3=.;PS4=.;PM1=.;PM2=.;PM3=.;PM4=.;PM5=.;PM6=.;PP1=.;PP2=.;PP3=.;PP4=.;PP5=.;BA1=.;BS1=.;BS2=.;BS3=.;BS4=.;BP1=.;BP2=.;BP3=.;BP4=.;BP5=.;BP6=.;BP7=.;esp6500siv2_ea=.;esp6500siv2_all=.;ExAC_ALL=0.1346;ExAC_AFR=0.0420;ExAC_AMR=0.1088;ExAC_EAS=0.1829;ExAC_FIN=0.1389;ExAC_NFE=0.1446;ExAC_OTH=0.1234;ExAC_SAS=0.1368;gnomAD_exome_ALL=0.1296;gnomAD_exome_AFR=0.0351;gnomAD_exome_AMR=0.0855;gnomAD_exome_ASJ=0.1562;gnomAD_exome_EAS=0.1602;gnomAD_exome_FIN=0.1292;gnomAD_exome_NFE=0.1493;gnomAD_exome_OTH=0.1390;gnomAD_exome_SAS=0.1339;gnomAD_genome_ALL=.;gnomAD_genome_AFR=.;gnomAD_genome_AMR=.;gnomAD_genome_ASJ=.;gnomAD_genome_EAS=.;gnomAD_genome_FIN=.;gnomAD_genome_NFE=.;gnomAD_genome_OTH=.;1000g2015aug_all=0.105232;MCAP=.;REVEL=.;GWAVA_region_score=0.21;GWAVA_tss_score=0.06;GWAVA_unmatched_score=182;ALLELE_END;ANNOVAR_DATE=2016-02-01;CADD13_RawScore=0.350070;CADD13_PHRED=6.167;ALLELE_END GT:AD:DP:GQ:PGT:PID:PL 0/0:.:32:90:.:.:0,90,255 0/1:.:25:99:.:.:255,0,255 0/0:.:35:93:.:.:0,93,255 +chr22 21349677 rs376419 C T 423 PASS AC=1;AF=0.167;AN=6;BaseQRankSum=-1.349e+00;ClippingRankSum=0.00;DB;DP=92;ExcessHet=3.0103;FS=1.623;MLEAC=1;MLEAF=0.167;MQ=60.00;MQRankSum=0.00;POSITIVE_TRAIN_SITE;QD=16.93;ReadPosRankSum=0.235;SOR=0.368;VQSLOD=8.80;culprit=MQRankSum;EFF=NON_SYNONYMOUS_CODING(MODERATE|MISSENSE|tCt/tTt|S92F|97|LZTR1|nonsense_mediated_decay|CODING|ENST00000415354|4|T),NON_SYNONYMOUS_CODING(MODERATE|MISSENSE|Ctc/Ttc|L82F|110|LZTR1|nonsense_mediated_decay|CODING|ENST00000439171|3|T|WARNING_TRANSCRIPT_NO_START_CODON),SPLICE_SITE_REGION+EXON(LOW|||||LZTR1|retained_intron|CODING|ENST00000464807|2|T),UPSTREAM(MODIFIER||400|||LZTR1|retained_intron|CODING|ENST00000498649||T),UPSTREAM(MODIFIER||608||157|LZTR1|protein_coding|CODING|ENST00000415817||T|WARNING_TRANSCRIPT_NO_START_CODON),DOWNSTREAM(MODIFIER||4384||309|THAP7|protein_coding|CODING|ENST00000215742||T),DOWNSTREAM(MODIFIER||3703||117|LZTR1|nonsense_mediated_decay|CODING|ENST00000414985||T),DOWNSTREAM(MODIFIER||3709|||LZTR1|processed_transcript|CODING|ENST00000480895||T),DOWNSTREAM(MODIFIER||2540|||LZTR1|processed_transcript|CODING|ENST00000497716||T),DOWNSTREAM(MODIFIER||2856|||LZTR1|retained_intron|CODING|ENST00000461510||T),DOWNSTREAM(MODIFIER||1088|||LZTR1|retained_intron|CODING|ENST00000492480||T),DOWNSTREAM(MODIFIER||3716|||THAP7|retained_intron|CODING|ENST00000498406||T),DOWNSTREAM(MODIFIER||4385|||THAP7|retained_intron|CODING|ENST00000471073||T),DOWNSTREAM(MODIFIER||4389||309|THAP7|protein_coding|CODING|ENST00000399133||T),DOWNSTREAM(MODIFIER||4414|||THAP7|retained_intron|CODING|ENST00000476667||T),DOWNSTREAM(MODIFIER||4842|||THAP7|retained_intron|CODING|ENST00000466670||T),DOWNSTREAM(MODIFIER||4884|||THAP7|retained_intron|CODING|ENST00000488975||T),INTRON(MODIFIER||||840|LZTR1|protein_coding|CODING|ENST00000215739|16|T),INTRON(MODIFIER|||||LZTR1|processed_transcript|CODING|ENST00000479606|17|T),INTRON(MODIFIER||||821|LZTR1|protein_coding|CODING|ENST00000389355|15|T),INTRON(MODIFIER|||||LZTR1|retained_intron|CODING|ENST00000495142|2|T),INTRON(MODIFIER|||||LZTR1|retained_intron|CODING|ENST00000491432|2|T),INTRON(MODIFIER||||54|LZTR1|nonsense_mediated_decay|CODING|ENST00000452988|1|T|WARNING_TRANSCRIPT_NO_START_CODON),EXON(MODIFIER|||||LZTR1|retained_intron|CODING|ENST00000463909|1|T);ANNOVAR_DATE=2016-02-01;Func.refGene=intronic;Gene.refGene=LZTR1;GeneDetail.refGene=.;ExonicFunc.refGene=.;AAChange.refGene=.;SIFT_score=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_pred=.;RadialSVM_score=.;RadialSVM_pred=.;LR_score=.;LR_pred=.;VEST3_score=.;CADD_raw=.;CADD_phred=.;GERP++_RS=.;phyloP46way_placental=.;phyloP100way_vertebrate=.;SiPhy_29way_logOdds=.;SIFT_score=.;SIFT_converted_rankscore=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_rankscore=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_rankscore=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_converted_rankscore=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_converted_rankscore=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_score_rankscore=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_converted_rankscore=.;FATHMM_pred=.;PROVEAN_score=.;PROVEAN_converted_rankscore=.;PROVEAN_pred=.;VEST3_score=.;VEST3_rankscore=.;MetaSVM_score=.;MetaSVM_rankscore=.;MetaSVM_pred=.;MetaLR_score=.;MetaLR_rankscore=.;MetaLR_pred=.;M-CAP_score=.;M-CAP_rankscore=.;M-CAP_pred=.;CADD_raw=.;CADD_raw_rankscore=.;CADD_phred=.;DANN_score=.;DANN_rankscore=.;fathmm-MKL_coding_score=.;fathmm-MKL_coding_rankscore=.;fathmm-MKL_coding_pred=.;Eigen_coding_or_noncoding=.;Eigen-raw=.;Eigen-PC-raw=.;GenoCanyon_score=.;GenoCanyon_score_rankscore=.;integrated_fitCons_score=.;integrated_fitCons_score_rankscore=.;integrated_confidence_value=.;GERP++_RS=.;GERP++_RS_rankscore=.;phyloP100way_vertebrate=.;phyloP100way_vertebrate_rankscore=.;phyloP20way_mammalian=.;phyloP20way_mammalian_rankscore=.;phastCons100way_vertebrate=.;phastCons100way_vertebrate_rankscore=.;phastCons20way_mammalian=.;phastCons20way_mammalian_rankscore=.;SiPhy_29way_logOdds=.;SiPhy_29way_logOdds_rankscore=.;Interpro_domain=.;GTEx_V6_gene=.;GTEx_V6_tissue=.;dbscSNV_ADA_SCORE=.;dbscSNV_RF_SCORE=.;InterVar(automated)=.;PVS1=.;PS1=.;PS2=.;PS3=.;PS4=.;PM1=.;PM2=.;PM3=.;PM4=.;PM5=.;PM6=.;PP1=.;PP2=.;PP3=.;PP4=.;PP5=.;BA1=.;BS1=.;BS2=.;BS3=.;BS4=.;BP1=.;BP2=.;BP3=.;BP4=.;BP5=.;BP6=.;BP7=.;esp6500siv2_ea=.;esp6500siv2_all=.;ExAC_ALL=0.1347;ExAC_AFR=0.0420;ExAC_AMR=0.1088;ExAC_EAS=0.1829;ExAC_FIN=0.1389;ExAC_NFE=0.1447;ExAC_OTH=0.1234;ExAC_SAS=0.1368;gnomAD_exome_ALL=0.1296;gnomAD_exome_AFR=0.0351;gnomAD_exome_AMR=0.0855;gnomAD_exome_ASJ=0.1563;gnomAD_exome_EAS=0.1602;gnomAD_exome_FIN=0.1292;gnomAD_exome_NFE=0.1493;gnomAD_exome_OTH=0.1391;gnomAD_exome_SAS=0.1339;gnomAD_genome_ALL=.;gnomAD_genome_AFR=.;gnomAD_genome_AMR=.;gnomAD_genome_ASJ=.;gnomAD_genome_EAS=.;gnomAD_genome_FIN=.;gnomAD_genome_NFE=.;gnomAD_genome_OTH=.;1000g2015aug_all=0.105232;MCAP=.;REVEL=.;GWAVA_region_score=0.19;GWAVA_tss_score=0.08;GWAVA_unmatched_score=182;ALLELE_END;ANNOVAR_DATE=2016-02-01;CADD13_RawScore=0.349663;CADD13_PHRED=6.163;ALLELE_END GT:AD:DP:GQ:PGT:PID:PL 0/0:.:32:90:.:.:0,90,255 0/1:.:25:99:.:.:255,0,255 0/0:.:35:93:.:.:0,93,255 +chr22 22262093 rs76843711 C A 1.17e+03 PASS AC=2;AF=0.333;AN=6;BaseQRankSum=3.06;ClippingRankSum=0.00;DB;DP=117;ExcessHet=3.9794;FS=2.960;MLEAC=2;MLEAF=0.333;MQ=60.00;MQRankSum=0.00;POSITIVE_TRAIN_SITE;QD=14.26;ReadPosRankSum=-1.830e-01;SOR=1.127;VQSLOD=9.04;culprit=MQRankSum;EFF=INTERGENIC(MODIFIER||||||||||A);ANNOVAR_DATE=2016-02-01;Func.refGene=intergenic;Gene.refGene=MAPK1,PPM1F;GeneDetail.refGene=dist\x3d40123\x3bdist\x3d11699;ExonicFunc.refGene=.;AAChange.refGene=.;SIFT_score=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_pred=.;RadialSVM_score=.;RadialSVM_pred=.;LR_score=.;LR_pred=.;VEST3_score=.;CADD_raw=.;CADD_phred=.;GERP++_RS=.;phyloP46way_placental=.;phyloP100way_vertebrate=.;SiPhy_29way_logOdds=.;SIFT_score=.;SIFT_converted_rankscore=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_rankscore=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_rankscore=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_converted_rankscore=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_converted_rankscore=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_score_rankscore=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_converted_rankscore=.;FATHMM_pred=.;PROVEAN_score=.;PROVEAN_converted_rankscore=.;PROVEAN_pred=.;VEST3_score=.;VEST3_rankscore=.;MetaSVM_score=.;MetaSVM_rankscore=.;MetaSVM_pred=.;MetaLR_score=.;MetaLR_rankscore=.;MetaLR_pred=.;M-CAP_score=.;M-CAP_rankscore=.;M-CAP_pred=.;CADD_raw=.;CADD_raw_rankscore=.;CADD_phred=.;DANN_score=.;DANN_rankscore=.;fathmm-MKL_coding_score=.;fathmm-MKL_coding_rankscore=.;fathmm-MKL_coding_pred=.;Eigen_coding_or_noncoding=.;Eigen-raw=.;Eigen-PC-raw=.;GenoCanyon_score=.;GenoCanyon_score_rankscore=.;integrated_fitCons_score=.;integrated_fitCons_score_rankscore=.;integrated_confidence_value=.;GERP++_RS=.;GERP++_RS_rankscore=.;phyloP100way_vertebrate=.;phyloP100way_vertebrate_rankscore=.;phyloP20way_mammalian=.;phyloP20way_mammalian_rankscore=.;phastCons100way_vertebrate=.;phastCons100way_vertebrate_rankscore=.;phastCons20way_mammalian=.;phastCons20way_mammalian_rankscore=.;SiPhy_29way_logOdds=.;SiPhy_29way_logOdds_rankscore=.;Interpro_domain=.;GTEx_V6_gene=.;GTEx_V6_tissue=.;dbscSNV_ADA_SCORE=.;dbscSNV_RF_SCORE=.;InterVar(automated)=.;PVS1=.;PS1=.;PS2=.;PS3=.;PS4=.;PM1=.;PM2=.;PM3=.;PM4=.;PM5=.;PM6=.;PP1=.;PP2=.;PP3=.;PP4=.;PP5=.;BA1=.;BS1=.;BS2=.;BS3=.;BS4=.;BP1=.;BP2=.;BP3=.;BP4=.;BP5=.;BP6=.;BP7=.;esp6500siv2_ea=.;esp6500siv2_all=.;ExAC_ALL=.;ExAC_AFR=.;ExAC_AMR=.;ExAC_EAS=.;ExAC_FIN=.;ExAC_NFE=.;ExAC_OTH=.;ExAC_SAS=.;gnomAD_exome_ALL=.;gnomAD_exome_AFR=.;gnomAD_exome_AMR=.;gnomAD_exome_ASJ=.;gnomAD_exome_EAS=.;gnomAD_exome_FIN=.;gnomAD_exome_NFE=.;gnomAD_exome_OTH=.;gnomAD_exome_SAS=.;gnomAD_genome_ALL=.;gnomAD_genome_AFR=.;gnomAD_genome_AMR=.;gnomAD_genome_ASJ=.;gnomAD_genome_EAS=.;gnomAD_genome_FIN=.;gnomAD_genome_NFE=.;gnomAD_genome_OTH=.;1000g2015aug_all=0.0696885;MCAP=.;REVEL=.;GWAVA_region_score=0.3;GWAVA_tss_score=0.12;GWAVA_unmatched_score=182;ALLELE_END;ANNOVAR_DATE=2016-02-01;CADD13_RawScore=0.097641;CADD13_PHRED=3.583;ALLELE_END GT:AD:DP:GQ:PL 0/0:.:34:99:0,99,255 0/1:.:42:99:255,0,255 0/1:.:40:99:255,0,255 +chr22 23247169 rs527511481 T G 719 PASS AC=1;AF=0.167;AN=6;BaseQRankSum=2.62;ClippingRankSum=0.00;DB;DP=121;ExcessHet=3.6798;FS=10.117;MLEAC=1;MLEAF=0.167;MQ=49.77;MQRankSum=-4.022e+00;NEGATIVE_TRAIN_SITE;QD=25.67;ReadPosRankSum=-9.600e-02;SOR=2.252;VQSLOD=-2.025e+00;culprit=SOR;EFF=NON_SYNONYMOUS_CODING(MODERATE|MISSENSE|Tgg/Ggg|W39G|49|IGLJ3|IG_J_gene|CODING|ENST00000390324|1|G|WARNING_TRANSCRIPT_INCOMPLETE),UPSTREAM(MODIFIER||1343||105|IGLC3|IG_C_gene|CODING|ENST00000390325||G|WARNING_TRANSCRIPT_NO_START_CODON),DOWNSTREAM(MODIFIER||3552||105|IGLC2|IG_C_gene|CODING|ENST00000390323||G|WARNING_TRANSCRIPT_NO_START_CODON);ANNOVAR_DATE=2016-02-01;Func.refGene=intergenic;Gene.refGene=IGLL5,RSPH14;GeneDetail.refGene=dist\x3d9156\x3bdist\x3d154424;ExonicFunc.refGene=.;AAChange.refGene=.;SIFT_score=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_pred=.;RadialSVM_score=.;RadialSVM_pred=.;LR_score=.;LR_pred=.;VEST3_score=.;CADD_raw=.;CADD_phred=.;GERP++_RS=.;phyloP46way_placental=.;phyloP100way_vertebrate=.;SiPhy_29way_logOdds=.;SIFT_score=.;SIFT_converted_rankscore=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_rankscore=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_rankscore=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_converted_rankscore=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_converted_rankscore=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_score_rankscore=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_converted_rankscore=.;FATHMM_pred=.;PROVEAN_score=.;PROVEAN_converted_rankscore=.;PROVEAN_pred=.;VEST3_score=.;VEST3_rankscore=.;MetaSVM_score=.;MetaSVM_rankscore=.;MetaSVM_pred=.;MetaLR_score=.;MetaLR_rankscore=.;MetaLR_pred=.;M-CAP_score=.;M-CAP_rankscore=.;M-CAP_pred=.;CADD_raw=.;CADD_raw_rankscore=.;CADD_phred=.;DANN_score=.;DANN_rankscore=.;fathmm-MKL_coding_score=.;fathmm-MKL_coding_rankscore=.;fathmm-MKL_coding_pred=.;Eigen_coding_or_noncoding=.;Eigen-raw=.;Eigen-PC-raw=.;GenoCanyon_score=.;GenoCanyon_score_rankscore=.;integrated_fitCons_score=.;integrated_fitCons_score_rankscore=.;integrated_confidence_value=.;GERP++_RS=.;GERP++_RS_rankscore=.;phyloP100way_vertebrate=.;phyloP100way_vertebrate_rankscore=.;phyloP20way_mammalian=.;phyloP20way_mammalian_rankscore=.;phastCons100way_vertebrate=.;phastCons100way_vertebrate_rankscore=.;phastCons20way_mammalian=.;phastCons20way_mammalian_rankscore=.;SiPhy_29way_logOdds=.;SiPhy_29way_logOdds_rankscore=.;Interpro_domain=.;GTEx_V6_gene=.;GTEx_V6_tissue=.;dbscSNV_ADA_SCORE=.;dbscSNV_RF_SCORE=.;InterVar(automated)=.;PVS1=.;PS1=.;PS2=.;PS3=.;PS4=.;PM1=.;PM2=.;PM3=.;PM4=.;PM5=.;PM6=.;PP1=.;PP2=.;PP3=.;PP4=.;PP5=.;BA1=.;BS1=.;BS2=.;BS3=.;BS4=.;BP1=.;BP2=.;BP3=.;BP4=.;BP5=.;BP6=.;BP7=.;esp6500siv2_ea=.;esp6500siv2_all=.;ExAC_ALL=0.1262;ExAC_AFR=0.2077;ExAC_AMR=0.0572;ExAC_EAS=0.1866;ExAC_FIN=0.17;ExAC_NFE=0.1171;ExAC_OTH=0.125;ExAC_SAS=0.1166;gnomAD_exome_ALL=0.0960;gnomAD_exome_AFR=0.2037;gnomAD_exome_AMR=0.0765;gnomAD_exome_ASJ=0.0650;gnomAD_exome_EAS=0.2503;gnomAD_exome_FIN=0.1001;gnomAD_exome_NFE=0.0779;gnomAD_exome_OTH=0.0925;gnomAD_exome_SAS=0.0712;gnomAD_genome_ALL=.;gnomAD_genome_AFR=.;gnomAD_genome_AMR=.;gnomAD_genome_ASJ=.;gnomAD_genome_EAS=.;gnomAD_genome_FIN=.;gnomAD_genome_NFE=.;gnomAD_genome_OTH=.;1000g2015aug_all=0.105032;MCAP=.;REVEL=.;GWAVA_region_score=.;GWAVA_tss_score=.;GWAVA_unmatched_score=.;ALLELE_END;ANNOVAR_DATE=2016-02-01;CADD13_RawScore=-2.133468;CADD13_PHRED=0.001;ALLELE_END GT:AD:DP:GQ:PGT:PID:PL 0/0:.:53:99:.:.:0,120,255 0/1:.:28:99:.:.:255,0,255 0/0:.:40:0:.:.:0,0,255 +chr22 23247170 rs540954398 G T 716 PASS AC=1;AF=0.167;AN=6;BaseQRankSum=1.73;ClippingRankSum=0.00;DB;DP=122;ExcessHet=3.0103;FS=9.423;MLEAC=1;MLEAF=0.167;MQ=49.47;MQRankSum=-4.088e+00;NEGATIVE_TRAIN_SITE;QD=24.70;ReadPosRankSum=-3.910e-01;SOR=1.911;VQSLOD=-2.392e+00;culprit=SOR;EFF=NON_SYNONYMOUS_CODING(MODERATE|MISSENSE|tGg/tTg|W39L|49|IGLJ3|IG_J_gene|CODING|ENST00000390324|1|T|WARNING_TRANSCRIPT_INCOMPLETE),UPSTREAM(MODIFIER||1342||105|IGLC3|IG_C_gene|CODING|ENST00000390325||T|WARNING_TRANSCRIPT_NO_START_CODON),DOWNSTREAM(MODIFIER||3553||105|IGLC2|IG_C_gene|CODING|ENST00000390323||T|WARNING_TRANSCRIPT_NO_START_CODON);ANNOVAR_DATE=2016-02-01;Func.refGene=intergenic;Gene.refGene=IGLL5,RSPH14;GeneDetail.refGene=dist\x3d9157\x3bdist\x3d154423;ExonicFunc.refGene=.;AAChange.refGene=.;SIFT_score=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_pred=.;RadialSVM_score=.;RadialSVM_pred=.;LR_score=.;LR_pred=.;VEST3_score=.;CADD_raw=.;CADD_phred=.;GERP++_RS=.;phyloP46way_placental=.;phyloP100way_vertebrate=.;SiPhy_29way_logOdds=.;SIFT_score=.;SIFT_converted_rankscore=.;SIFT_pred=.;Polyphen2_HDIV_score=.;Polyphen2_HDIV_rankscore=.;Polyphen2_HDIV_pred=.;Polyphen2_HVAR_score=.;Polyphen2_HVAR_rankscore=.;Polyphen2_HVAR_pred=.;LRT_score=.;LRT_converted_rankscore=.;LRT_pred=.;MutationTaster_score=.;MutationTaster_converted_rankscore=.;MutationTaster_pred=.;MutationAssessor_score=.;MutationAssessor_score_rankscore=.;MutationAssessor_pred=.;FATHMM_score=.;FATHMM_converted_rankscore=.;FATHMM_pred=.;PROVEAN_score=.;PROVEAN_converted_rankscore=.;PROVEAN_pred=.;VEST3_score=.;VEST3_rankscore=.;MetaSVM_score=.;MetaSVM_rankscore=.;MetaSVM_pred=.;MetaLR_score=.;MetaLR_rankscore=.;MetaLR_pred=.;M-CAP_score=.;M-CAP_rankscore=.;M-CAP_pred=.;CADD_raw=.;CADD_raw_rankscore=.;CADD_phred=.;DANN_score=.;DANN_rankscore=.;fathmm-MKL_coding_score=.;fathmm-MKL_coding_rankscore=.;fathmm-MKL_coding_pred=.;Eigen_coding_or_noncoding=.;Eigen-raw=.;Eigen-PC-raw=.;GenoCanyon_score=.;GenoCanyon_score_rankscore=.;integrated_fitCons_score=.;integrated_fitCons_score_rankscore=.;integrated_confidence_value=.;GERP++_RS=.;GERP++_RS_rankscore=.;phyloP100way_vertebrate=.;phyloP100way_vertebrate_rankscore=.;phyloP20way_mammalian=.;phyloP20way_mammalian_rankscore=.;phastCons100way_vertebrate=.;phastCons100way_vertebrate_rankscore=.;phastCons20way_mammalian=.;phastCons20way_mammalian_rankscore=.;SiPhy_29way_logOdds=.;SiPhy_29way_logOdds_rankscore=.;Interpro_domain=.;GTEx_V6_gene=.;GTEx_V6_tissue=.;dbscSNV_ADA_SCORE=.;dbscSNV_RF_SCORE=.;InterVar(automated)=.;PVS1=.;PS1=.;PS2=.;PS3=.;PS4=.;PM1=.;PM2=.;PM3=.;PM4=.;PM5=.;PM6=.;PP1=.;PP2=.;PP3=.;PP4=.;PP5=.;BA1=.;BS1=.;BS2=.;BS3=.;BS4=.;BP1=.;BP2=.;BP3=.;BP4=.;BP5=.;BP6=.;BP7=.;esp6500siv2_ea=.;esp6500siv2_all=.;ExAC_ALL=0.1225;ExAC_AFR=0.1998;ExAC_AMR=0.0548;ExAC_EAS=0.1777;ExAC_FIN=0.1607;ExAC_NFE=0.1143;ExAC_OTH=0.1207;ExAC_SAS=0.1145;gnomAD_exome_ALL=0.0906;gnomAD_exome_AFR=0.1949;gnomAD_exome_AMR=0.0726;gnomAD_exome_ASJ=0.0615;gnomAD_exome_EAS=0.2403;gnomAD_exome_FIN=0.0928;gnomAD_exome_NFE=0.0729;gnomAD_exome_OTH=0.0885;gnomAD_exome_SAS=0.0669;gnomAD_genome_ALL=.;gnomAD_genome_AFR=.;gnomAD_genome_AMR=.;gnomAD_genome_ASJ=.;gnomAD_genome_EAS=.;gnomAD_genome_FIN=.;gnomAD_genome_NFE=.;gnomAD_genome_OTH=.;1000g2015aug_all=0.103035;MCAP=.;REVEL=.;GWAVA_region_score=.;GWAVA_tss_score=.;GWAVA_unmatched_score=.;ALLELE_END;ANNOVAR_DATE=2016-02-01;CADD13_RawScore=-1.839588;CADD13_PHRED=0.002;ALLELE_END GT:AD:DP:GQ:PGT:PID:PL 0/0:.:53:99:.:.:0,120,255 0/1:.:29:99:.:.:255,0,255 0/0:.:40:15:.:.:0,15,255