changeset 0:ee4ef1fc23c6 draft

Uploaded
author greg
date Tue, 21 Apr 2020 10:14:11 -0400
parents
children 770834ba75e4
files .shed.yml test-data/SRR1792272_zc.vcf test-data/SRR8073662_zc.vcf test-data/all_vcf.fasta test-data/input_zc_vcf.vcf test-data/json_all_vcf.json test-data/json_avg_mq_all_vcf.json test-data/output_fasta.fasta test-data/output_json_avg_mq.json test-data/output_json_snps.json test-data/output_summary.html tool-data/vsnp_excel.loc.sample tool_data_table_conf.xml.sample vsnp_get_snps.py vsnp_get_snps.xml
diffstat 15 files changed, 3894 insertions(+), 0 deletions(-) [+]
line wrap: on
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/.shed.yml	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,11 @@
+name: vsnp_get_snps
+owner: greg
+description: |
+  Contains a tool that collects quality parsimonious SNPs from vcf files and outputs alignment files in fasta format.
+homepage_url: https://github.com/USDA-VS/vSNP
+long_description: |
+  Contains a tool that collects quality parsimonious SNPs from vcf files and outputs alignment files in fasta format.
+remote_repository_url: https://github.com/gregvonkuster/galaxy_tools/tree/master/tools/sequence_analysis/vsnp/vsnp_get_snps
+type: unrestricted
+categories:
+  - Sequence Analysis
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/SRR1792272_zc.vcf	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,1058 @@
+##fileformat=VCFv4.2
+##fileDate=20190125
+##source=freeBayes v1.2.0-dirty
+##reference=/scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR1792272/NC_002945v4.fasta
+##contig=<ID=NC_002945.4,length=4349904>
+##phasing=none
+##commandline="freebayes -E -1 -e 1 -u --strict-vcf -f /scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR1792272/NC_002945v4.fasta /scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR1792272/SRR1792272-nodup.bam --region NC_002945.4:0-100000
+##filter="QUAL > 20
+##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
+##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
+##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
+##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
+##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
+##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
+##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
+##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
+##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
+##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
+##INFO=<ID=QR,Number=1,Type=Integer,Description="Reference allele quality sum in phred">
+##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
+##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
+##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
+##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
+##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
+##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
+##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
+##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
+##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
+##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
+##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
+##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
+##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
+##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
+##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
+##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
+##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
+##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
+##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
+##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
+##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
+##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
+##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
+##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
+##INFO=<ID=technology.ILLUMINA,Number=A,Type=Float,Description="Fraction of observations supporting the alternate observed in reads from ILLUMINA">
+##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
+##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
+##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
+##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
+##FORMAT=<ID=QR,Number=1,Type=Integer,Description="Sum of quality of the reference observations">
+##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
+##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
+##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	SRR1792272
+NC_002945.4	1057	.	A	G	8671.65	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=288;CIGAR=1X;DP=289;DPB=289;DPRA=0;EPP=3.04046;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=403.858;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=9688;QR=0;RO=0;RPL=157;RPP=8.10723;RPPR=0;RPR=131;RUN=1;SAF=146;SAP=3.13094;SAR=142;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:289:0,288:0:0:288:9688:-871.673,-86.6966,0
+NC_002945.4	4480	.	T	C	4873.39	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=163;CIGAR=1X;DP=163;DPB=163;DPRA=0;EPP=3.1302;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=230.571;PAIRED=0.97546;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=5469;QR=0;RO=0;RPL=94;RPP=11.3365;RPPR=0;RPR=69;RUN=1;SAF=72;SAP=7.81951;SAR=91;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:163:0,163:0:0:163:5469:-492.275,-49.0679,0
+NC_002945.4	8741	.	T	C	6443.62	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=221;CIGAR=1X;DP=224;DPB=224;DPRA=0;EPP=24.7152;EPPR=5.18177;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=306.56;PAIRED=0.977376;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=7233;QR=12;RO=1;RPL=118;RPP=5.22108;RPPR=5.18177;RPR=103;RUN=1;SAF=115;SAP=3.80618;SAR=106;SRF=0;SRP=5.18177;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:224:1,221:1:12:221:7233:-649.748,-65.752,0
+NC_002945.4	29061	.	C	T	6683.56	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=218;CIGAR=1X;DP=221;DPB=221;DPRA=0;EPP=8.74777;EPPR=7.35324;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=59.5;NS=1;NUMALT=1;ODDS=298.686;PAIRED=0.954128;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=7482;QR=24;RO=2;RPL=103;RPP=4.44467;RPPR=7.35324;RPR=115;RUN=1;SAF=108;SAP=3.05014;SAR=110;SRF=0;SRP=7.35324;SRR=2;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:221:2,218:2:24:218:7482:-671.072,-64.0666,0
+NC_002945.4	29471	.	N	.	.	.	.	GT	./.
+NC_002945.4	29472	.	N	.	.	.	.	GT	./.
+NC_002945.4	29473	.	N	.	.	.	.	GT	./.
+NC_002945.4	29474	.	N	.	.	.	.	GT	./.
+NC_002945.4	29475	.	N	.	.	.	.	GT	./.
+NC_002945.4	29476	.	N	.	.	.	.	GT	./.
+NC_002945.4	29477	.	N	.	.	.	.	GT	./.
+NC_002945.4	29478	.	N	.	.	.	.	GT	./.
+NC_002945.4	29479	.	N	.	.	.	.	GT	./.
+NC_002945.4	29480	.	N	.	.	.	.	GT	./.
+NC_002945.4	29481	.	N	.	.	.	.	GT	./.
+NC_002945.4	29482	.	N	.	.	.	.	GT	./.
+NC_002945.4	29483	.	N	.	.	.	.	GT	./.
+NC_002945.4	29484	.	N	.	.	.	.	GT	./.
+NC_002945.4	29485	.	N	.	.	.	.	GT	./.
+NC_002945.4	29486	.	N	.	.	.	.	GT	./.
+NC_002945.4	29487	.	N	.	.	.	.	GT	./.
+NC_002945.4	29488	.	N	.	.	.	.	GT	./.
+NC_002945.4	29489	.	N	.	.	.	.	GT	./.
+NC_002945.4	29490	.	N	.	.	.	.	GT	./.
+NC_002945.4	29491	.	N	.	.	.	.	GT	./.
+NC_002945.4	29492	.	N	.	.	.	.	GT	./.
+NC_002945.4	29493	.	N	.	.	.	.	GT	./.
+NC_002945.4	29494	.	N	.	.	.	.	GT	./.
+NC_002945.4	29495	.	N	.	.	.	.	GT	./.
+NC_002945.4	29496	.	N	.	.	.	.	GT	./.
+NC_002945.4	29497	.	N	.	.	.	.	GT	./.
+NC_002945.4	29498	.	N	.	.	.	.	GT	./.
+NC_002945.4	29499	.	N	.	.	.	.	GT	./.
+NC_002945.4	29500	.	N	.	.	.	.	GT	./.
+NC_002945.4	29501	.	N	.	.	.	.	GT	./.
+NC_002945.4	29502	.	N	.	.	.	.	GT	./.
+NC_002945.4	29503	.	N	.	.	.	.	GT	./.
+NC_002945.4	29504	.	N	.	.	.	.	GT	./.
+NC_002945.4	29505	.	N	.	.	.	.	GT	./.
+NC_002945.4	29506	.	N	.	.	.	.	GT	./.
+NC_002945.4	29507	.	N	.	.	.	.	GT	./.
+NC_002945.4	29508	.	N	.	.	.	.	GT	./.
+NC_002945.4	29509	.	N	.	.	.	.	GT	./.
+NC_002945.4	29510	.	N	.	.	.	.	GT	./.
+NC_002945.4	29511	.	N	.	.	.	.	GT	./.
+NC_002945.4	29512	.	N	.	.	.	.	GT	./.
+NC_002945.4	29513	.	N	.	.	.	.	GT	./.
+NC_002945.4	29514	.	N	.	.	.	.	GT	./.
+NC_002945.4	29515	.	N	.	.	.	.	GT	./.
+NC_002945.4	29516	.	N	.	.	.	.	GT	./.
+NC_002945.4	29517	.	N	.	.	.	.	GT	./.
+NC_002945.4	29518	.	N	.	.	.	.	GT	./.
+NC_002945.4	29519	.	N	.	.	.	.	GT	./.
+NC_002945.4	29520	.	N	.	.	.	.	GT	./.
+NC_002945.4	29521	.	N	.	.	.	.	GT	./.
+NC_002945.4	29522	.	N	.	.	.	.	GT	./.
+NC_002945.4	29523	.	N	.	.	.	.	GT	./.
+NC_002945.4	29524	.	N	.	.	.	.	GT	./.
+NC_002945.4	29525	.	N	.	.	.	.	GT	./.
+NC_002945.4	29526	.	N	.	.	.	.	GT	./.
+NC_002945.4	29527	.	N	.	.	.	.	GT	./.
+NC_002945.4	29528	.	N	.	.	.	.	GT	./.
+NC_002945.4	29529	.	N	.	.	.	.	GT	./.
+NC_002945.4	29530	.	N	.	.	.	.	GT	./.
+NC_002945.4	29531	.	N	.	.	.	.	GT	./.
+NC_002945.4	29532	.	N	.	.	.	.	GT	./.
+NC_002945.4	29533	.	N	.	.	.	.	GT	./.
+NC_002945.4	29534	.	N	.	.	.	.	GT	./.
+NC_002945.4	29535	.	N	.	.	.	.	GT	./.
+NC_002945.4	29536	.	N	.	.	.	.	GT	./.
+NC_002945.4	29537	.	N	.	.	.	.	GT	./.
+NC_002945.4	29538	.	N	.	.	.	.	GT	./.
+NC_002945.4	29539	.	N	.	.	.	.	GT	./.
+NC_002945.4	29540	.	N	.	.	.	.	GT	./.
+NC_002945.4	29541	.	N	.	.	.	.	GT	./.
+NC_002945.4	29542	.	N	.	.	.	.	GT	./.
+NC_002945.4	29543	.	N	.	.	.	.	GT	./.
+NC_002945.4	29544	.	N	.	.	.	.	GT	./.
+NC_002945.4	29545	.	N	.	.	.	.	GT	./.
+NC_002945.4	29546	.	N	.	.	.	.	GT	./.
+NC_002945.4	29547	.	N	.	.	.	.	GT	./.
+NC_002945.4	29548	.	N	.	.	.	.	GT	./.
+NC_002945.4	29549	.	N	.	.	.	.	GT	./.
+NC_002945.4	29550	.	N	.	.	.	.	GT	./.
+NC_002945.4	29551	.	N	.	.	.	.	GT	./.
+NC_002945.4	29552	.	N	.	.	.	.	GT	./.
+NC_002945.4	29553	.	N	.	.	.	.	GT	./.
+NC_002945.4	29554	.	N	.	.	.	.	GT	./.
+NC_002945.4	29555	.	N	.	.	.	.	GT	./.
+NC_002945.4	29556	.	N	.	.	.	.	GT	./.
+NC_002945.4	29557	.	N	.	.	.	.	GT	./.
+NC_002945.4	29558	.	N	.	.	.	.	GT	./.
+NC_002945.4	29559	.	N	.	.	.	.	GT	./.
+NC_002945.4	29560	.	N	.	.	.	.	GT	./.
+NC_002945.4	29561	.	N	.	.	.	.	GT	./.
+NC_002945.4	29562	.	N	.	.	.	.	GT	./.
+NC_002945.4	29563	.	N	.	.	.	.	GT	./.
+NC_002945.4	29564	.	N	.	.	.	.	GT	./.
+NC_002945.4	29565	.	N	.	.	.	.	GT	./.
+NC_002945.4	29566	.	N	.	.	.	.	GT	./.
+NC_002945.4	29567	.	N	.	.	.	.	GT	./.
+NC_002945.4	29568	.	N	.	.	.	.	GT	./.
+NC_002945.4	29569	.	N	.	.	.	.	GT	./.
+NC_002945.4	29570	.	N	.	.	.	.	GT	./.
+NC_002945.4	29571	.	N	.	.	.	.	GT	./.
+NC_002945.4	29572	.	N	.	.	.	.	GT	./.
+NC_002945.4	29573	.	N	.	.	.	.	GT	./.
+NC_002945.4	29574	.	N	.	.	.	.	GT	./.
+NC_002945.4	29575	.	N	.	.	.	.	GT	./.
+NC_002945.4	29576	.	N	.	.	.	.	GT	./.
+NC_002945.4	29577	.	N	.	.	.	.	GT	./.
+NC_002945.4	29578	.	N	.	.	.	.	GT	./.
+NC_002945.4	29579	.	N	.	.	.	.	GT	./.
+NC_002945.4	29580	.	N	.	.	.	.	GT	./.
+NC_002945.4	29581	.	N	.	.	.	.	GT	./.
+NC_002945.4	29582	.	N	.	.	.	.	GT	./.
+NC_002945.4	29583	.	N	.	.	.	.	GT	./.
+NC_002945.4	29584	.	N	.	.	.	.	GT	./.
+NC_002945.4	29585	.	N	.	.	.	.	GT	./.
+NC_002945.4	29586	.	N	.	.	.	.	GT	./.
+NC_002945.4	29587	.	N	.	.	.	.	GT	./.
+NC_002945.4	29588	.	N	.	.	.	.	GT	./.
+NC_002945.4	29589	.	N	.	.	.	.	GT	./.
+NC_002945.4	29590	.	N	.	.	.	.	GT	./.
+NC_002945.4	29591	.	N	.	.	.	.	GT	./.
+NC_002945.4	29592	.	N	.	.	.	.	GT	./.
+NC_002945.4	29593	.	N	.	.	.	.	GT	./.
+NC_002945.4	29594	.	N	.	.	.	.	GT	./.
+NC_002945.4	29595	.	N	.	.	.	.	GT	./.
+NC_002945.4	29596	.	N	.	.	.	.	GT	./.
+NC_002945.4	29597	.	N	.	.	.	.	GT	./.
+NC_002945.4	29598	.	N	.	.	.	.	GT	./.
+NC_002945.4	29599	.	N	.	.	.	.	GT	./.
+NC_002945.4	29600	.	N	.	.	.	.	GT	./.
+NC_002945.4	29601	.	N	.	.	.	.	GT	./.
+NC_002945.4	29602	.	N	.	.	.	.	GT	./.
+NC_002945.4	29603	.	N	.	.	.	.	GT	./.
+NC_002945.4	29604	.	N	.	.	.	.	GT	./.
+NC_002945.4	29605	.	N	.	.	.	.	GT	./.
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+NC_002945.4	332160	.	N	.	.	.	.	GT	./.
+NC_002945.4	332161	.	N	.	.	.	.	GT	./.
+NC_002945.4	332162	.	N	.	.	.	.	GT	./.
+NC_002945.4	332163	.	N	.	.	.	.	GT	./.
+NC_002945.4	332164	.	N	.	.	.	.	GT	./.
+NC_002945.4	332165	.	N	.	.	.	.	GT	./.
+NC_002945.4	332166	.	N	.	.	.	.	GT	./.
+NC_002945.4	332167	.	N	.	.	.	.	GT	./.
+NC_002945.4	332168	.	N	.	.	.	.	GT	./.
+NC_002945.4	332169	.	N	.	.	.	.	GT	./.
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+NC_002945.4	332172	.	N	.	.	.	.	GT	./.
+NC_002945.4	332173	.	N	.	.	.	.	GT	./.
+NC_002945.4	332174	.	N	.	.	.	.	GT	./.
+NC_002945.4	332175	.	N	.	.	.	.	GT	./.
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+NC_002945.4	332178	.	N	.	.	.	.	GT	./.
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+NC_002945.4	332192	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333461	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333466	.	N	.	.	.	.	GT	./.
+NC_002945.4	333467	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333484	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333523	.	N	.	.	.	.	GT	./.
+NC_002945.4	333629	.	N	.	.	.	.	GT	./.
+NC_002945.4	333630	.	N	.	.	.	.	GT	./.
+NC_002945.4	333631	.	N	.	.	.	.	GT	./.
+NC_002945.4	333632	.	N	.	.	.	.	GT	./.
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+NC_002945.4	336585	.	N	.	.	.	.	GT	./.
+NC_002945.4	336586	.	N	.	.	.	.	GT	./.
+NC_002945.4	336587	.	N	.	.	.	.	GT	./.
+NC_002945.4	336588	.	N	.	.	.	.	GT	./.
+NC_002945.4	336589	.	N	.	.	.	.	GT	./.
+NC_002945.4	336590	.	N	.	.	.	.	GT	./.
+NC_002945.4	336591	.	N	.	.	.	.	GT	./.
+NC_002945.4	336592	.	N	.	.	.	.	GT	./.
+NC_002945.4	336593	.	N	.	.	.	.	GT	./.
+NC_002945.4	336594	.	N	.	.	.	.	GT	./.
+NC_002945.4	336595	.	N	.	.	.	.	GT	./.
+NC_002945.4	336596	.	N	.	.	.	.	GT	./.
+NC_002945.4	336597	.	N	.	.	.	.	GT	./.
+NC_002945.4	336598	.	N	.	.	.	.	GT	./.
+NC_002945.4	336599	.	N	.	.	.	.	GT	./.
+NC_002945.4	336600	.	N	.	.	.	.	GT	./.
+NC_002945.4	336601	.	N	.	.	.	.	GT	./.
+NC_002945.4	336602	.	N	.	.	.	.	GT	./.
+NC_002945.4	339375	.	N	.	.	.	.	GT	./.
+NC_002945.4	339376	.	N	.	.	.	.	GT	./.
+NC_002945.4	339377	.	N	.	.	.	.	GT	./.
+NC_002945.4	339378	.	N	.	.	.	.	GT	./.
+NC_002945.4	339379	.	N	.	.	.	.	GT	./.
+NC_002945.4	339380	.	N	.	.	.	.	GT	./.
+NC_002945.4	339381	.	N	.	.	.	.	GT	./.
+NC_002945.4	339382	.	N	.	.	.	.	GT	./.
+NC_002945.4	339383	.	N	.	.	.	.	GT	./.
+NC_002945.4	339384	.	N	.	.	.	.	GT	./.
+NC_002945.4	339385	.	N	.	.	.	.	GT	./.
+NC_002945.4	339386	.	N	.	.	.	.	GT	./.
+NC_002945.4	339387	.	N	.	.	.	.	GT	./.
+NC_002945.4	339388	.	N	.	.	.	.	GT	./.
+NC_002945.4	339389	.	N	.	.	.	.	GT	./.
+NC_002945.4	339390	.	N	.	.	.	.	GT	./.
+NC_002945.4	339391	.	N	.	.	.	.	GT	./.
+NC_002945.4	339392	.	N	.	.	.	.	GT	./.
+NC_002945.4	339393	.	N	.	.	.	.	GT	./.
+NC_002945.4	339394	.	N	.	.	.	.	GT	./.
+NC_002945.4	339395	.	N	.	.	.	.	GT	./.
+NC_002945.4	339396	.	N	.	.	.	.	GT	./.
+NC_002945.4	339397	.	N	.	.	.	.	GT	./.
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+NC_002945.4	339400	.	N	.	.	.	.	GT	./.
+NC_002945.4	339401	.	N	.	.	.	.	GT	./.
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+NC_002945.4	339405	.	N	.	.	.	.	GT	./.
+NC_002945.4	339406	.	N	.	.	.	.	GT	./.
+NC_002945.4	339407	.	N	.	.	.	.	GT	./.
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+NC_002945.4	339410	.	N	.	.	.	.	GT	./.
+NC_002945.4	339411	.	N	.	.	.	.	GT	./.
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+NC_002945.4	624648	.	N	.	.	.	.	GT	./.
+NC_002945.4	624649	.	N	.	.	.	.	GT	./.
+NC_002945.4	624650	.	N	.	.	.	.	GT	./.
+NC_002945.4	624651	.	N	.	.	.	.	GT	./.
+NC_002945.4	624652	.	N	.	.	.	.	GT	./.
+NC_002945.4	624653	.	N	.	.	.	.	GT	./.
+NC_002945.4	624654	.	N	.	.	.	.	GT	./.
+NC_002945.4	624655	.	N	.	.	.	.	GT	./.
+NC_002945.4	624656	.	N	.	.	.	.	GT	./.
+NC_002945.4	624657	.	N	.	.	.	.	GT	./.
+NC_002945.4	624658	.	N	.	.	.	.	GT	./.
+NC_002945.4	624659	.	N	.	.	.	.	GT	./.
+NC_002945.4	624660	.	N	.	.	.	.	GT	./.
+NC_002945.4	624661	.	N	.	.	.	.	GT	./.
+NC_002945.4	624662	.	N	.	.	.	.	GT	./.
+NC_002945.4	624663	.	N	.	.	.	.	GT	./.
+NC_002945.4	624664	.	N	.	.	.	.	GT	./.
+NC_002945.4	624665	.	N	.	.	.	.	GT	./.
+NC_002945.4	624666	.	N	.	.	.	.	GT	./.
+NC_002945.4	624667	.	N	.	.	.	.	GT	./.
+NC_002945.4	624668	.	N	.	.	.	.	GT	./.
+NC_002945.4	624669	.	N	.	.	.	.	GT	./.
+NC_002945.4	624670	.	N	.	.	.	.	GT	./.
+NC_002945.4	624671	.	N	.	.	.	.	GT	./.
+NC_002945.4	624672	.	N	.	.	.	.	GT	./.
+NC_002945.4	624673	.	N	.	.	.	.	GT	./.
+NC_002945.4	624674	.	N	.	.	.	.	GT	./.
+NC_002945.4	624675	.	N	.	.	.	.	GT	./.
+NC_002945.4	624676	.	N	.	.	.	.	GT	./.
+NC_002945.4	624677	.	N	.	.	.	.	GT	./.
+NC_002945.4	624678	.	N	.	.	.	.	GT	./.
+NC_002945.4	624679	.	N	.	.	.	.	GT	./.
+NC_002945.4	624901	.	N	.	.	.	.	GT	./.
+NC_002945.4	624902	.	N	.	.	.	.	GT	./.
+NC_002945.4	624903	.	N	.	.	.	.	GT	./.
+NC_002945.4	624904	.	N	.	.	.	.	GT	./.
+NC_002945.4	624905	.	N	.	.	.	.	GT	./.
+NC_002945.4	624906	.	N	.	.	.	.	GT	./.
+NC_002945.4	624907	.	N	.	.	.	.	GT	./.
+NC_002945.4	624908	.	N	.	.	.	.	GT	./.
+NC_002945.4	624909	.	N	.	.	.	.	GT	./.
+NC_002945.4	624910	.	N	.	.	.	.	GT	./.
+NC_002945.4	624911	.	N	.	.	.	.	GT	./.
+NC_002945.4	641896	.	A	C	6646.66	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=217;CIGAR=1X;DP=217;DPB=217;DPRA=0;EPP=5.26183;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=305.431;PAIRED=0.990783;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7442;QR=0;RO=0;RPL=94;RPP=11.426;RPPR=0;RPR=123;RUN=1;SAF=101;SAP=5.26183;SAR=116;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:217:0,217:0:0:217:7442:-669.755,-65.3235,0
+NC_002945.4	642875	.	C	G	7980.41	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=255;CIGAR=1X;DP=256;DPB=256;DPRA=0;EPP=4.92631;EPPR=5.18177;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=352.807;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=8971;QR=14;RO=1;RPL=164;RPP=48.3898;RPPR=5.18177;RPR=91;RUN=1;SAF=125;SAP=3.22319;SAR=130;SRF=0;SRP=5.18177;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:256:1,255:1:14:255:8971:-805.839,-75.6637,0
+NC_002945.4	644245	.	C	G	5488.97	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=190;CIGAR=1X;DP=192;DPB=192;DPRA=0;EPP=3.05602;EPPR=3.0103;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=247.117;PAIRED=0.978947;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=6207;QR=76;RO=2;RPL=95;RPP=3.0103;RPPR=7.35324;RPR=95;RUN=1;SAF=99;SAP=3.74174;SAR=91;SRF=1;SRP=3.0103;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:192:2,190:2:76:190:6207:-551.485,-50.5829,0
+NC_002945.4	649910	.	T	C	6733.74	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=223;CIGAR=1X;DP=224;DPB=224;DPRA=0;EPP=4.65594;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=313.749;PAIRED=0.986547;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7540;QR=0;RO=0;RPL=127;RPP=12.3681;RPPR=0;RPR=96;RUN=1;SAF=118;SAP=4.65594;SAR=105;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:224:0,223:0:0:223:7540:-678.455,-67.1297,0
+NC_002945.4	652349	.	G	C	8112.27	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=262;CIGAR=1X;DP=264;DPB=264;DPRA=0;EPP=4.63476;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=367.814;PAIRED=0.996183;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=9069;QR=0;RO=0;RPL=125;RPP=4.20378;RPPR=0;RPR=137;RUN=1;SAF=143;SAP=7.78422;SAR=119;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:264:0,262:0:0:262:9069:-815.907,-78.8699,0
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/SRR8073662_zc.vcf	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,1011 @@
+##fileformat=VCFv4.2
+##fileDate=20190125
+##source=freeBayes v1.2.0-dirty
+##reference=/scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR8073662/NC_002945v4.fasta
+##contig=<ID=NC_002945.4,length=4349904>
+##phasing=none
+##commandline="freebayes -E -1 -e 1 -u --strict-vcf -f /scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR8073662/NC_002945v4.fasta /scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR8073662/SRR8073662-nodup.bam --region NC_002945.4:0-100000
+##filter="QUAL > 20
+##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
+##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
+##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
+##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
+##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
+##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
+##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
+##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
+##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
+##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
+##INFO=<ID=QR,Number=1,Type=Integer,Description="Reference allele quality sum in phred">
+##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
+##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
+##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
+##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
+##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
+##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
+##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
+##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
+##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
+##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
+##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
+##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
+##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
+##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
+##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
+##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
+##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
+##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
+##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
+##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
+##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
+##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
+##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
+##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
+##INFO=<ID=technology.ILLUMINA,Number=A,Type=Float,Description="Fraction of observations supporting the alternate observed in reads from ILLUMINA">
+##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
+##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
+##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
+##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
+##FORMAT=<ID=QR,Number=1,Type=Integer,Description="Sum of quality of the reference observations">
+##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
+##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
+##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	SRR8073662
+NC_002945.4	1057	.	A	G	1991.37	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=78;CIGAR=1X;DP=80;DPB=80;DPRA=0;EPP=4.01252;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=112.736;PAIRED=0.961538;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=2256;QR=0;RO=0;RPL=41;RPP=3.45573;RPPR=0;RPR=37;RUN=1;SAF=47;SAP=10.1372;SAR=31;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:80:0,78:0:0:78:2256:-203.125,-23.4803,0
+NC_002945.4	4480	.	T	C	1266.94	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=48;CIGAR=1X;DP=49;DPB=49;DPRA=0;EPP=9.52472;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=71.1473;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1446;QR=0;RO=0;RPL=26;RPP=3.73412;RPPR=0;RPR=22;RUN=1;SAF=24;SAP=3.0103;SAR=24;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:49:0,48:0:0:48:1446:-130.232,-14.4494,0
+NC_002945.4	8741	.	T	C	1656.81	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=68;CIGAR=1X;DP=68;DPB=68;DPRA=0;EPP=44.396;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=98.8732;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1927;QR=0;RO=0;RPL=35;RPP=3.13803;RPPR=0;RPR=33;RUN=1;SAF=41;SAP=9.26925;SAR=27;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:68:0,68:0:0:68:1927:-173.649,-20.47,0
+NC_002945.4	29061	.	C	T	1418.86	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=55;CIGAR=1X;DP=56;DPB=56;DPRA=0;EPP=3.36563;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=59.8909;MQMR=0;NS=1;NUMALT=1;ODDS=80.8514;PAIRED=0.854545;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1614;QR=0;RO=0;RPL=22;RPP=7.78754;RPPR=0;RPR=33;RUN=1;SAF=29;SAP=3.36563;SAR=26;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:56:0,55:0:0:55:1614:-145.339,-16.5567,0
+NC_002945.4	29470	.	N	.	.	.	.	GT	./.
+NC_002945.4	29471	.	N	.	.	.	.	GT	./.
+NC_002945.4	29472	.	N	.	.	.	.	GT	./.
+NC_002945.4	29473	.	N	.	.	.	.	GT	./.
+NC_002945.4	29474	.	N	.	.	.	.	GT	./.
+NC_002945.4	29475	.	N	.	.	.	.	GT	./.
+NC_002945.4	29476	.	N	.	.	.	.	GT	./.
+NC_002945.4	29477	.	N	.	.	.	.	GT	./.
+NC_002945.4	29478	.	N	.	.	.	.	GT	./.
+NC_002945.4	29479	.	N	.	.	.	.	GT	./.
+NC_002945.4	29480	.	N	.	.	.	.	GT	./.
+NC_002945.4	29481	.	N	.	.	.	.	GT	./.
+NC_002945.4	29482	.	N	.	.	.	.	GT	./.
+NC_002945.4	29483	.	N	.	.	.	.	GT	./.
+NC_002945.4	29484	.	N	.	.	.	.	GT	./.
+NC_002945.4	29485	.	N	.	.	.	.	GT	./.
+NC_002945.4	29486	.	N	.	.	.	.	GT	./.
+NC_002945.4	29487	.	N	.	.	.	.	GT	./.
+NC_002945.4	29488	.	N	.	.	.	.	GT	./.
+NC_002945.4	29489	.	N	.	.	.	.	GT	./.
+NC_002945.4	29490	.	N	.	.	.	.	GT	./.
+NC_002945.4	29491	.	N	.	.	.	.	GT	./.
+NC_002945.4	29492	.	N	.	.	.	.	GT	./.
+NC_002945.4	29493	.	N	.	.	.	.	GT	./.
+NC_002945.4	29494	.	N	.	.	.	.	GT	./.
+NC_002945.4	29495	.	N	.	.	.	.	GT	./.
+NC_002945.4	29496	.	N	.	.	.	.	GT	./.
+NC_002945.4	29497	.	N	.	.	.	.	GT	./.
+NC_002945.4	29498	.	N	.	.	.	.	GT	./.
+NC_002945.4	29499	.	N	.	.	.	.	GT	./.
+NC_002945.4	29500	.	N	.	.	.	.	GT	./.
+NC_002945.4	29501	.	N	.	.	.	.	GT	./.
+NC_002945.4	29502	.	N	.	.	.	.	GT	./.
+NC_002945.4	29503	.	N	.	.	.	.	GT	./.
+NC_002945.4	29504	.	N	.	.	.	.	GT	./.
+NC_002945.4	29505	.	N	.	.	.	.	GT	./.
+NC_002945.4	29506	.	N	.	.	.	.	GT	./.
+NC_002945.4	29507	.	N	.	.	.	.	GT	./.
+NC_002945.4	29508	.	N	.	.	.	.	GT	./.
+NC_002945.4	29509	.	N	.	.	.	.	GT	./.
+NC_002945.4	29510	.	N	.	.	.	.	GT	./.
+NC_002945.4	29511	.	N	.	.	.	.	GT	./.
+NC_002945.4	29512	.	N	.	.	.	.	GT	./.
+NC_002945.4	29513	.	N	.	.	.	.	GT	./.
+NC_002945.4	29514	.	N	.	.	.	.	GT	./.
+NC_002945.4	29515	.	N	.	.	.	.	GT	./.
+NC_002945.4	29516	.	N	.	.	.	.	GT	./.
+NC_002945.4	29517	.	N	.	.	.	.	GT	./.
+NC_002945.4	29518	.	N	.	.	.	.	GT	./.
+NC_002945.4	29519	.	N	.	.	.	.	GT	./.
+NC_002945.4	29520	.	N	.	.	.	.	GT	./.
+NC_002945.4	29521	.	N	.	.	.	.	GT	./.
+NC_002945.4	29522	.	N	.	.	.	.	GT	./.
+NC_002945.4	29523	.	N	.	.	.	.	GT	./.
+NC_002945.4	29524	.	N	.	.	.	.	GT	./.
+NC_002945.4	29525	.	N	.	.	.	.	GT	./.
+NC_002945.4	29526	.	N	.	.	.	.	GT	./.
+NC_002945.4	29527	.	N	.	.	.	.	GT	./.
+NC_002945.4	29528	.	N	.	.	.	.	GT	./.
+NC_002945.4	29529	.	N	.	.	.	.	GT	./.
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+NC_002945.4	179885	.	G	A	1895.35	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=77;CIGAR=1X;DP=82;DPB=82;DPRA=0;EPP=3.0385;EPPR=13.8677;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=98.8465;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=2153;QR=60;RO=5;RPL=34;RPP=5.29458;RPPR=13.8677;RPR=43;RUN=1;SAF=41;SAP=3.71532;SAR=36;SRF=5;SRP=13.8677;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:82:5,77:5:60:77:2153:-188.447,-19.1645,0
+NC_002945.4	189083	.	A	G	1178.55	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=46;CIGAR=1X;DP=46;DPB=46;DPRA=0;EPP=12.2627;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=68.3747;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1359;QR=0;RO=0;RPL=17;RPP=9.80795;RPPR=0;RPR=29;RUN=1;SAF=27;SAP=6.03148;SAR=19;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:46:0,46:0:0:46:1359:-122.54,-13.8474,0
+NC_002945.4	192177	.	A	G	1304.14	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=46;CIGAR=1X;DP=46;DPB=46;DPRA=0;EPP=15.095;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=68.3747;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1491;QR=0;RO=0;RPL=24;RPP=3.19912;RPPR=0;RPR=22;RUN=1;SAF=23;SAP=3.0103;SAR=23;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:46:0,46:0:0:46:1491:-134.434,-13.8474,0
+NC_002945.4	198890	.	T	G	1479.47	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=52;CIGAR=1X;DP=52;DPB=52;DPRA=0;EPP=5.68288;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=76.6925;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1720;QR=0;RO=0;RPL=32;RPP=9.02361;RPPR=0;RPR=20;RUN=1;SAF=12;SAP=35.7494;SAR=40;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:52:0,52:0:0:52:1720:-155.06,-15.6536,0
+NC_002945.4	223919	.	C	T	937.27	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=39;CIGAR=1X;DP=41;DPB=41;DPRA=0;EPP=4.40227;EPPR=5.18177;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=55.9607;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=1080;QR=12;RO=1;RPL=22;RPP=4.40227;RPPR=5.18177;RPR=17;RUN=1;SAF=24;SAP=7.52028;SAR=15;SRF=0;SRP=5.18177;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:41:1,39:1:12:39:1080:-96.2285,-10.9612,0
+NC_002945.4	228109	.	C	T	1608.55	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=61;CIGAR=1X;DP=62;DPB=62;DPRA=0;EPP=7.31765;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=89.1691;PAIRED=0.983607;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1829;QR=0;RO=0;RPL=32;RPP=3.33068;RPPR=0;RPR=29;RUN=1;SAF=25;SAP=7.31765;SAR=36;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:62:0,61:0:0:61:1829:-164.716,-18.3628,0
+NC_002945.4	230661	.	A	G	1378.76	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=49;CIGAR=1X;DP=49;DPB=49;DPRA=0;EPP=6.59988;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=72.5336;PAIRED=0.959184;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1571;QR=0;RO=0;RPL=23;RPP=3.40914;RPPR=0;RPR=26;RUN=1;SAF=30;SAP=8.37251;SAR=19;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:49:0,49:0:0:49:1571:-141.635,-14.7505,0
+NC_002945.4	232188	.	G	C	899.6439999999999	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=37;CIGAR=1X;DP=37;DPB=37;DPRA=0;EPP=3.5385;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=55.8981;PAIRED=0.972973;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1041;QR=0;RO=0;RPL=22;RPP=5.88603;RPPR=0;RPR=15;RUN=1;SAF=12;SAP=12.9286;SAR=25;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:37:0,37:0:0:37:1041:-93.938,-11.1381,0
+NC_002945.4	295519	.	T	C	1828.28	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=70;CIGAR=1X;DP=71;DPB=71;DPRA=0;EPP=7.47733;EPPR=5.18177;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=97.1647;PAIRED=0.985714;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=2082;QR=16;RO=1;RPL=29;RPP=7.47733;RPPR=5.18177;RPR=41;RUN=1;SAF=32;SAP=4.12706;SAR=38;SRF=0;SRP=5.18177;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:71:1,70:1:16:70:2082:-185.986,-19.7731,0
+NC_002945.4	299636	.	A	G	2260.51	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=76;CIGAR=1X;DP=76;DPB=76;DPRA=0;EPP=4.03889;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=109.964;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=2561;QR=0;RO=0;RPL=27;RPP=16.8392;RPPR=0;RPR=49;RUN=1;SAF=36;SAP=3.46745;SAR=40;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:76:0,76:0:0:76:2561:-230.702,-22.8783,0
+NC_002945.4	304339	.	G	A	2005.61	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=74;CIGAR=1X;DP=77;DPB=77;DPRA=0;EPP=3.47981;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=107.191;PAIRED=0.986486;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=2271;QR=0;RO=0;RPL=45;RPP=10.5224;RPPR=0;RPR=29;RUN=1;SAF=38;SAP=3.12768;SAR=36;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:77:0,74:0:0:74:2271:-204.468,-22.2762,0
+NC_002945.4	306688	.	N	.	.	.	.	GT	./.
+NC_002945.4	306689	.	N	.	.	.	.	GT	./.
+NC_002945.4	306690	.	N	.	.	.	.	GT	./.
+NC_002945.4	306691	.	N	.	.	.	.	GT	./.
+NC_002945.4	306692	.	N	.	.	.	.	GT	./.
+NC_002945.4	306693	.	N	.	.	.	.	GT	./.
+NC_002945.4	306694	.	N	.	.	.	.	GT	./.
+NC_002945.4	306695	.	N	.	.	.	.	GT	./.
+NC_002945.4	306696	.	N	.	.	.	.	GT	./.
+NC_002945.4	306697	.	N	.	.	.	.	GT	./.
+NC_002945.4	306698	.	N	.	.	.	.	GT	./.
+NC_002945.4	306699	.	N	.	.	.	.	GT	./.
+NC_002945.4	306700	.	N	.	.	.	.	GT	./.
+NC_002945.4	306701	.	N	.	.	.	.	GT	./.
+NC_002945.4	306702	.	N	.	.	.	.	GT	./.
+NC_002945.4	306703	.	N	.	.	.	.	GT	./.
+NC_002945.4	306704	.	N	.	.	.	.	GT	./.
+NC_002945.4	306705	.	N	.	.	.	.	GT	./.
+NC_002945.4	306706	.	N	.	.	.	.	GT	./.
+NC_002945.4	306707	.	N	.	.	.	.	GT	./.
+NC_002945.4	306708	.	N	.	.	.	.	GT	./.
+NC_002945.4	306709	.	N	.	.	.	.	GT	./.
+NC_002945.4	306710	.	N	.	.	.	.	GT	./.
+NC_002945.4	319911	.	C	T	1185.93	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=43;CIGAR=1X;DP=43;DPB=43;DPRA=0;EPP=3.0608;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=64.2158;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=1346;QR=0;RO=0;RPL=20;RPP=3.46479;RPPR=0;RPR=23;RUN=1;SAF=22;SAP=3.0608;SAR=21;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:43:0,43:0:0:43:1346:-121.399,-12.9443,0
+NC_002945.4	332124	.	C	T	162.344	.	AB=0.7;ABP=6.48466;AC=1;AF=0.5;AN=2;AO=7;CIGAR=1X;DP=10;DPB=10;DPRA=0;EPP=5.80219;EPPR=9.52472;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=12.1823;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=225;QR=36;RO=3;RPL=7;RPP=18.2106;RPPR=9.52472;RPR=0;RUN=1;SAF=2;SAP=5.80219;SAR=5;SRF=3;SRP=9.52472;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	0/1:10:3,7:3:36:7:225:-17.552,0,-0.349682
+NC_002945.4	332128	.	C	G	158.059	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=8;CIGAR=1X;DP=8;DPB=8;DPRA=0;EPP=3.0103;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=15.6955;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=212;QR=0;RO=0;RPL=8;RPP=20.3821;RPPR=0;RPR=0;RUN=1;SAF=4;SAP=3.0103;SAR=4;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:8:0,8:0:0:8:212:-19.3404,-2.40824,0
+NC_002945.4	332144	.	C	T	23.1525	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=3;CIGAR=1X;DP=4;DPB=4;DPRA=0;EPP=9.52472;EPPR=5.18177;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=5.3259;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=57;QR=12;RO=1;RPL=3;RPP=9.52472;RPPR=5.18177;RPR=0;RUN=1;SAF=3;SAP=9.52472;SAR=0;SRF=1;SRP=5.18177;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:4:1,3:1:12:3:57:-4.11919,-0.00412644,0
+NC_002945.4	332145	.	G	T	43.4124	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=4;CIGAR=1X;DP=4;DPB=4;DPRA=0;EPP=11.6962;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=9.99598;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=86;QR=0;RO=0;RPL=4;RPP=11.6962;RPPR=0;RPR=0;RUN=1;SAF=4;SAP=11.6962;SAR=0;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:4:0,4:0:0:4:86:-7.95356,-1.20412,0
+NC_002945.4	332154	.	G	C	48.5003	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=3;CIGAR=1X;DP=3;DPB=3;DPRA=0;EPP=9.52472;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=8.76405;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=81;QR=0;RO=0;RPL=3;RPP=9.52472;RPPR=0;RPR=0;RUN=1;SAF=3;SAP=9.52472;SAR=0;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:3:0,3:0:0:3:81:-7.55923,-0.90309,0
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/all_vcf.fasta	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,4 @@
+>SRR1792272_zc
+>dataset_
+>SRR8073662_zc
+>root
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/input_zc_vcf.vcf	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,1087 @@
+##fileformat=VCFv4.2
+##fileDate=20190125
+##source=freeBayes v1.2.0-dirty
+##reference=/scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR1791698/NC_002945v4.fasta
+##contig=<ID=NC_002945.4,length=4349904>
+##phasing=none
+##commandline="freebayes -E -1 -e 1 -u --strict-vcf -f /scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR1791698/NC_002945v4.fasta /scratch/analysis_staging/a_script/vcf_test_files_sra_downloaded_2019-01-23/SRR1791698/SRR1791698-nodup.bam --region NC_002945.4:0-100000
+##filter="QUAL > 20
+##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
+##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
+##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
+##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
+##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
+##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
+##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
+##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
+##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
+##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
+##INFO=<ID=QR,Number=1,Type=Integer,Description="Reference allele quality sum in phred">
+##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
+##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
+##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
+##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
+##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
+##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
+##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
+##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
+##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
+##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
+##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
+##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
+##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
+##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
+##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
+##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
+##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternate allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
+##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
+##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
+##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
+##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
+##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
+##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
+##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
+##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
+##INFO=<ID=technology.ILLUMINA,Number=A,Type=Float,Description="Fraction of observations supporting the alternate observed in reads from ILLUMINA">
+##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
+##FORMAT=<ID=GQ,Number=1,Type=Integer,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
+##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
+##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
+##FORMAT=<ID=QR,Number=1,Type=Integer,Description="Sum of quality of the reference observations">
+##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
+##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
+##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	SRR1791698
+NC_002945.4	1057	.	A	G	7624.7	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=262;CIGAR=1X;DP=265;DPB=265;DPRA=0;EPP=4.20378;EPPR=5.18177;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=363.221;PAIRED=1;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=8526;QR=12;RO=1;RPL=140;RPP=5.69563;RPPR=5.18177;RPR=122;RUN=1;SAF=139;SAP=5.13204;SAR=123;SRF=0;SRP=5.18177;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:265:1,262:1:12:262:8526:-766.088,-78.0909,0
+NC_002945.4	4480	.	T	C	4142.4	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=144;CIGAR=1X;DP=145;DPB=145;DPRA=0;EPP=3.07062;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=204.232;PAIRED=0.993056;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=4647;QR=0;RO=0;RPL=79;RPP=5.96592;RPPR=0;RPR=65;RUN=1;SAF=72;SAP=3.0103;SAR=72;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:145:0,144:0:0:144:4647:-418.074,-43.3483,0
+NC_002945.4	8741	.	T	C	5252.19	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=184;CIGAR=1X;DP=186;DPB=186;DPRA=0;EPP=16.6528;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=259.683;PAIRED=0.98913;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=5901;QR=0;RO=0;RPL=81;RPP=8.72222;RPPR=0;RPR=103;RUN=1;SAF=98;SAP=4.70971;SAR=86;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:186:0,184:0:0:184:5901:-531.016,-55.3895,0
+NC_002945.4	29061	.	C	T	4714.63	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=163;CIGAR=1X;DP=164;DPB=164;DPRA=0;EPP=3.1302;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=230.571;PAIRED=0.969325;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=5311;QR=0;RO=0;RPL=59;RPP=29.9872;RPPR=0;RPR=104;RUN=1;SAF=83;SAP=3.1302;SAR=80;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:164:0,163:0:0:163:5311:-477.817,-49.0679,0
+NC_002945.4	29471	.	N	.	.	.	.	GT	./.
+NC_002945.4	29472	.	N	.	.	.	.	GT	./.
+NC_002945.4	29473	.	N	.	.	.	.	GT	./.
+NC_002945.4	29474	.	N	.	.	.	.	GT	./.
+NC_002945.4	29475	.	N	.	.	.	.	GT	./.
+NC_002945.4	29476	.	N	.	.	.	.	GT	./.
+NC_002945.4	29477	.	N	.	.	.	.	GT	./.
+NC_002945.4	29478	.	N	.	.	.	.	GT	./.
+NC_002945.4	29479	.	N	.	.	.	.	GT	./.
+NC_002945.4	29480	.	N	.	.	.	.	GT	./.
+NC_002945.4	29481	.	N	.	.	.	.	GT	./.
+NC_002945.4	29482	.	N	.	.	.	.	GT	./.
+NC_002945.4	29483	.	N	.	.	.	.	GT	./.
+NC_002945.4	29484	.	N	.	.	.	.	GT	./.
+NC_002945.4	29485	.	N	.	.	.	.	GT	./.
+NC_002945.4	29486	.	N	.	.	.	.	GT	./.
+NC_002945.4	29487	.	N	.	.	.	.	GT	./.
+NC_002945.4	29488	.	N	.	.	.	.	GT	./.
+NC_002945.4	29489	.	N	.	.	.	.	GT	./.
+NC_002945.4	29490	.	N	.	.	.	.	GT	./.
+NC_002945.4	29491	.	N	.	.	.	.	GT	./.
+NC_002945.4	29492	.	N	.	.	.	.	GT	./.
+NC_002945.4	29493	.	N	.	.	.	.	GT	./.
+NC_002945.4	29494	.	N	.	.	.	.	GT	./.
+NC_002945.4	29495	.	N	.	.	.	.	GT	./.
+NC_002945.4	29496	.	N	.	.	.	.	GT	./.
+NC_002945.4	29497	.	N	.	.	.	.	GT	./.
+NC_002945.4	29498	.	N	.	.	.	.	GT	./.
+NC_002945.4	29499	.	N	.	.	.	.	GT	./.
+NC_002945.4	29500	.	N	.	.	.	.	GT	./.
+NC_002945.4	29501	.	N	.	.	.	.	GT	./.
+NC_002945.4	29502	.	N	.	.	.	.	GT	./.
+NC_002945.4	29503	.	N	.	.	.	.	GT	./.
+NC_002945.4	29504	.	N	.	.	.	.	GT	./.
+NC_002945.4	29505	.	N	.	.	.	.	GT	./.
+NC_002945.4	29506	.	N	.	.	.	.	GT	./.
+NC_002945.4	29507	.	N	.	.	.	.	GT	./.
+NC_002945.4	29508	.	N	.	.	.	.	GT	./.
+NC_002945.4	29509	.	N	.	.	.	.	GT	./.
+NC_002945.4	29510	.	N	.	.	.	.	GT	./.
+NC_002945.4	29511	.	N	.	.	.	.	GT	./.
+NC_002945.4	29512	.	N	.	.	.	.	GT	./.
+NC_002945.4	29513	.	N	.	.	.	.	GT	./.
+NC_002945.4	29514	.	N	.	.	.	.	GT	./.
+NC_002945.4	29515	.	N	.	.	.	.	GT	./.
+NC_002945.4	29516	.	N	.	.	.	.	GT	./.
+NC_002945.4	29517	.	N	.	.	.	.	GT	./.
+NC_002945.4	29518	.	N	.	.	.	.	GT	./.
+NC_002945.4	29519	.	N	.	.	.	.	GT	./.
+NC_002945.4	29520	.	N	.	.	.	.	GT	./.
+NC_002945.4	29521	.	N	.	.	.	.	GT	./.
+NC_002945.4	29522	.	N	.	.	.	.	GT	./.
+NC_002945.4	29523	.	N	.	.	.	.	GT	./.
+NC_002945.4	29524	.	N	.	.	.	.	GT	./.
+NC_002945.4	29525	.	N	.	.	.	.	GT	./.
+NC_002945.4	29526	.	N	.	.	.	.	GT	./.
+NC_002945.4	29527	.	N	.	.	.	.	GT	./.
+NC_002945.4	29528	.	N	.	.	.	.	GT	./.
+NC_002945.4	29529	.	N	.	.	.	.	GT	./.
+NC_002945.4	29530	.	N	.	.	.	.	GT	./.
+NC_002945.4	29531	.	N	.	.	.	.	GT	./.
+NC_002945.4	29532	.	N	.	.	.	.	GT	./.
+NC_002945.4	29533	.	N	.	.	.	.	GT	./.
+NC_002945.4	29534	.	N	.	.	.	.	GT	./.
+NC_002945.4	29535	.	N	.	.	.	.	GT	./.
+NC_002945.4	29536	.	N	.	.	.	.	GT	./.
+NC_002945.4	29537	.	N	.	.	.	.	GT	./.
+NC_002945.4	29538	.	N	.	.	.	.	GT	./.
+NC_002945.4	29539	.	N	.	.	.	.	GT	./.
+NC_002945.4	29540	.	N	.	.	.	.	GT	./.
+NC_002945.4	29541	.	N	.	.	.	.	GT	./.
+NC_002945.4	29542	.	N	.	.	.	.	GT	./.
+NC_002945.4	29543	.	N	.	.	.	.	GT	./.
+NC_002945.4	29544	.	N	.	.	.	.	GT	./.
+NC_002945.4	29545	.	N	.	.	.	.	GT	./.
+NC_002945.4	29546	.	N	.	.	.	.	GT	./.
+NC_002945.4	29547	.	N	.	.	.	.	GT	./.
+NC_002945.4	29548	.	N	.	.	.	.	GT	./.
+NC_002945.4	29549	.	N	.	.	.	.	GT	./.
+NC_002945.4	29550	.	N	.	.	.	.	GT	./.
+NC_002945.4	29551	.	N	.	.	.	.	GT	./.
+NC_002945.4	29552	.	N	.	.	.	.	GT	./.
+NC_002945.4	29553	.	N	.	.	.	.	GT	./.
+NC_002945.4	29554	.	N	.	.	.	.	GT	./.
+NC_002945.4	29555	.	N	.	.	.	.	GT	./.
+NC_002945.4	29556	.	N	.	.	.	.	GT	./.
+NC_002945.4	29557	.	N	.	.	.	.	GT	./.
+NC_002945.4	29558	.	N	.	.	.	.	GT	./.
+NC_002945.4	29559	.	N	.	.	.	.	GT	./.
+NC_002945.4	29560	.	N	.	.	.	.	GT	./.
+NC_002945.4	29561	.	N	.	.	.	.	GT	./.
+NC_002945.4	29562	.	N	.	.	.	.	GT	./.
+NC_002945.4	29563	.	N	.	.	.	.	GT	./.
+NC_002945.4	29564	.	N	.	.	.	.	GT	./.
+NC_002945.4	29565	.	N	.	.	.	.	GT	./.
+NC_002945.4	29566	.	N	.	.	.	.	GT	./.
+NC_002945.4	29567	.	N	.	.	.	.	GT	./.
+NC_002945.4	29568	.	N	.	.	.	.	GT	./.
+NC_002945.4	29569	.	N	.	.	.	.	GT	./.
+NC_002945.4	29570	.	N	.	.	.	.	GT	./.
+NC_002945.4	29571	.	N	.	.	.	.	GT	./.
+NC_002945.4	29572	.	N	.	.	.	.	GT	./.
+NC_002945.4	29573	.	N	.	.	.	.	GT	./.
+NC_002945.4	29574	.	N	.	.	.	.	GT	./.
+NC_002945.4	29575	.	N	.	.	.	.	GT	./.
+NC_002945.4	29576	.	N	.	.	.	.	GT	./.
+NC_002945.4	29577	.	N	.	.	.	.	GT	./.
+NC_002945.4	29578	.	N	.	.	.	.	GT	./.
+NC_002945.4	29579	.	N	.	.	.	.	GT	./.
+NC_002945.4	29580	.	N	.	.	.	.	GT	./.
+NC_002945.4	29581	.	N	.	.	.	.	GT	./.
+NC_002945.4	29582	.	N	.	.	.	.	GT	./.
+NC_002945.4	29583	.	N	.	.	.	.	GT	./.
+NC_002945.4	29584	.	N	.	.	.	.	GT	./.
+NC_002945.4	29585	.	N	.	.	.	.	GT	./.
+NC_002945.4	29586	.	N	.	.	.	.	GT	./.
+NC_002945.4	29587	.	N	.	.	.	.	GT	./.
+NC_002945.4	29588	.	N	.	.	.	.	GT	./.
+NC_002945.4	29589	.	N	.	.	.	.	GT	./.
+NC_002945.4	29590	.	N	.	.	.	.	GT	./.
+NC_002945.4	29591	.	N	.	.	.	.	GT	./.
+NC_002945.4	29592	.	N	.	.	.	.	GT	./.
+NC_002945.4	29593	.	N	.	.	.	.	GT	./.
+NC_002945.4	29594	.	N	.	.	.	.	GT	./.
+NC_002945.4	29595	.	N	.	.	.	.	GT	./.
+NC_002945.4	29596	.	N	.	.	.	.	GT	./.
+NC_002945.4	29597	.	N	.	.	.	.	GT	./.
+NC_002945.4	29598	.	N	.	.	.	.	GT	./.
+NC_002945.4	29599	.	N	.	.	.	.	GT	./.
+NC_002945.4	29600	.	N	.	.	.	.	GT	./.
+NC_002945.4	29601	.	N	.	.	.	.	GT	./.
+NC_002945.4	29602	.	N	.	.	.	.	GT	./.
+NC_002945.4	29603	.	N	.	.	.	.	GT	./.
+NC_002945.4	29604	.	N	.	.	.	.	GT	./.
+NC_002945.4	29605	.	N	.	.	.	.	GT	./.
+NC_002945.4	29606	.	N	.	.	.	.	GT	./.
+NC_002945.4	29607	.	N	.	.	.	.	GT	./.
+NC_002945.4	29608	.	N	.	.	.	.	GT	./.
+NC_002945.4	29609	.	N	.	.	.	.	GT	./.
+NC_002945.4	29610	.	N	.	.	.	.	GT	./.
+NC_002945.4	29611	.	N	.	.	.	.	GT	./.
+NC_002945.4	29612	.	N	.	.	.	.	GT	./.
+NC_002945.4	29613	.	N	.	.	.	.	GT	./.
+NC_002945.4	29614	.	N	.	.	.	.	GT	./.
+NC_002945.4	29615	.	N	.	.	.	.	GT	./.
+NC_002945.4	29616	.	N	.	.	.	.	GT	./.
+NC_002945.4	29617	.	N	.	.	.	.	GT	./.
+NC_002945.4	29618	.	N	.	.	.	.	GT	./.
+NC_002945.4	29619	.	N	.	.	.	.	GT	./.
+NC_002945.4	29620	.	N	.	.	.	.	GT	./.
+NC_002945.4	29621	.	N	.	.	.	.	GT	./.
+NC_002945.4	29622	.	N	.	.	.	.	GT	./.
+NC_002945.4	29623	.	N	.	.	.	.	GT	./.
+NC_002945.4	29624	.	N	.	.	.	.	GT	./.
+NC_002945.4	29625	.	N	.	.	.	.	GT	./.
+NC_002945.4	29626	.	N	.	.	.	.	GT	./.
+NC_002945.4	29627	.	N	.	.	.	.	GT	./.
+NC_002945.4	29628	.	N	.	.	.	.	GT	./.
+NC_002945.4	29629	.	N	.	.	.	.	GT	./.
+NC_002945.4	29630	.	N	.	.	.	.	GT	./.
+NC_002945.4	29631	.	N	.	.	.	.	GT	./.
+NC_002945.4	29632	.	N	.	.	.	.	GT	./.
+NC_002945.4	29633	.	N	.	.	.	.	GT	./.
+NC_002945.4	29634	.	N	.	.	.	.	GT	./.
+NC_002945.4	29635	.	N	.	.	.	.	GT	./.
+NC_002945.4	29636	.	N	.	.	.	.	GT	./.
+NC_002945.4	29637	.	N	.	.	.	.	GT	./.
+NC_002945.4	29638	.	N	.	.	.	.	GT	./.
+NC_002945.4	29639	.	N	.	.	.	.	GT	./.
+NC_002945.4	29640	.	N	.	.	.	.	GT	./.
+NC_002945.4	29641	.	N	.	.	.	.	GT	./.
+NC_002945.4	29642	.	N	.	.	.	.	GT	./.
+NC_002945.4	29643	.	N	.	.	.	.	GT	./.
+NC_002945.4	29644	.	N	.	.	.	.	GT	./.
+NC_002945.4	29645	.	N	.	.	.	.	GT	./.
+NC_002945.4	29646	.	N	.	.	.	.	GT	./.
+NC_002945.4	29647	.	N	.	.	.	.	GT	./.
+NC_002945.4	29648	.	N	.	.	.	.	GT	./.
+NC_002945.4	29649	.	N	.	.	.	.	GT	./.
+NC_002945.4	29650	.	N	.	.	.	.	GT	./.
+NC_002945.4	29651	.	N	.	.	.	.	GT	./.
+NC_002945.4	29652	.	N	.	.	.	.	GT	./.
+NC_002945.4	29653	.	N	.	.	.	.	GT	./.
+NC_002945.4	29654	.	N	.	.	.	.	GT	./.
+NC_002945.4	29655	.	N	.	.	.	.	GT	./.
+NC_002945.4	29656	.	N	.	.	.	.	GT	./.
+NC_002945.4	29657	.	N	.	.	.	.	GT	./.
+NC_002945.4	29658	.	N	.	.	.	.	GT	./.
+NC_002945.4	29659	.	N	.	.	.	.	GT	./.
+NC_002945.4	29660	.	N	.	.	.	.	GT	./.
+NC_002945.4	29661	.	N	.	.	.	.	GT	./.
+NC_002945.4	29662	.	N	.	.	.	.	GT	./.
+NC_002945.4	29663	.	N	.	.	.	.	GT	./.
+NC_002945.4	29664	.	N	.	.	.	.	GT	./.
+NC_002945.4	29665	.	N	.	.	.	.	GT	./.
+NC_002945.4	29666	.	N	.	.	.	.	GT	./.
+NC_002945.4	29667	.	N	.	.	.	.	GT	./.
+NC_002945.4	29668	.	N	.	.	.	.	GT	./.
+NC_002945.4	29669	.	N	.	.	.	.	GT	./.
+NC_002945.4	29670	.	N	.	.	.	.	GT	./.
+NC_002945.4	29671	.	N	.	.	.	.	GT	./.
+NC_002945.4	29672	.	N	.	.	.	.	GT	./.
+NC_002945.4	29673	.	N	.	.	.	.	GT	./.
+NC_002945.4	29674	.	N	.	.	.	.	GT	./.
+NC_002945.4	29675	.	N	.	.	.	.	GT	./.
+NC_002945.4	29676	.	N	.	.	.	.	GT	./.
+NC_002945.4	29677	.	N	.	.	.	.	GT	./.
+NC_002945.4	29678	.	N	.	.	.	.	GT	./.
+NC_002945.4	29679	.	N	.	.	.	.	GT	./.
+NC_002945.4	29680	.	N	.	.	.	.	GT	./.
+NC_002945.4	29681	.	N	.	.	.	.	GT	./.
+NC_002945.4	29682	.	N	.	.	.	.	GT	./.
+NC_002945.4	29683	.	N	.	.	.	.	GT	./.
+NC_002945.4	29684	.	N	.	.	.	.	GT	./.
+NC_002945.4	29685	.	N	.	.	.	.	GT	./.
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+NC_002945.4	29966	.	N	.	.	.	.	GT	./.
+NC_002945.4	29967	.	N	.	.	.	.	GT	./.
+NC_002945.4	29968	.	N	.	.	.	.	GT	./.
+NC_002945.4	29969	.	N	.	.	.	.	GT	./.
+NC_002945.4	29970	.	N	.	.	.	.	GT	./.
+NC_002945.4	29971	.	N	.	.	.	.	GT	./.
+NC_002945.4	29972	.	N	.	.	.	.	GT	./.
+NC_002945.4	29973	.	N	.	.	.	.	GT	./.
+NC_002945.4	29974	.	N	.	.	.	.	GT	./.
+NC_002945.4	29975	.	N	.	.	.	.	GT	./.
+NC_002945.4	29976	.	N	.	.	.	.	GT	./.
+NC_002945.4	29977	.	N	.	.	.	.	GT	./.
+NC_002945.4	29978	.	N	.	.	.	.	GT	./.
+NC_002945.4	29979	.	N	.	.	.	.	GT	./.
+NC_002945.4	29980	.	N	.	.	.	.	GT	./.
+NC_002945.4	29981	.	N	.	.	.	.	GT	./.
+NC_002945.4	29982	.	N	.	.	.	.	GT	./.
+NC_002945.4	29983	.	N	.	.	.	.	GT	./.
+NC_002945.4	29984	.	N	.	.	.	.	GT	./.
+NC_002945.4	29985	.	N	.	.	.	.	GT	./.
+NC_002945.4	29986	.	N	.	.	.	.	GT	./.
+NC_002945.4	29987	.	N	.	.	.	.	GT	./.
+NC_002945.4	29988	.	N	.	.	.	.	GT	./.
+NC_002945.4	29989	.	N	.	.	.	.	GT	./.
+NC_002945.4	29990	.	N	.	.	.	.	GT	./.
+NC_002945.4	29991	.	N	.	.	.	.	GT	./.
+NC_002945.4	29992	.	N	.	.	.	.	GT	./.
+NC_002945.4	29993	.	N	.	.	.	.	GT	./.
+NC_002945.4	29994	.	N	.	.	.	.	GT	./.
+NC_002945.4	29995	.	N	.	.	.	.	GT	./.
+NC_002945.4	29996	.	N	.	.	.	.	GT	./.
+NC_002945.4	29997	.	N	.	.	.	.	GT	./.
+NC_002945.4	29998	.	N	.	.	.	.	GT	./.
+NC_002945.4	29999	.	N	.	.	.	.	GT	./.
+NC_002945.4	30000	.	N	.	.	.	.	GT	./.
+NC_002945.4	30001	.	N	.	.	.	.	GT	./.
+NC_002945.4	30002	.	N	.	.	.	.	GT	./.
+NC_002945.4	30003	.	N	.	.	.	.	GT	./.
+NC_002945.4	30004	.	N	.	.	.	.	GT	./.
+NC_002945.4	30005	.	N	.	.	.	.	GT	./.
+NC_002945.4	30006	.	N	.	.	.	.	GT	./.
+NC_002945.4	30007	.	N	.	.	.	.	GT	./.
+NC_002945.4	30008	.	N	.	.	.	.	GT	./.
+NC_002945.4	30009	.	N	.	.	.	.	GT	./.
+NC_002945.4	30010	.	N	.	.	.	.	GT	./.
+NC_002945.4	30011	.	N	.	.	.	.	GT	./.
+NC_002945.4	30012	.	N	.	.	.	.	GT	./.
+NC_002945.4	30013	.	N	.	.	.	.	GT	./.
+NC_002945.4	30014	.	N	.	.	.	.	GT	./.
+NC_002945.4	30015	.	N	.	.	.	.	GT	./.
+NC_002945.4	30016	.	N	.	.	.	.	GT	./.
+NC_002945.4	30017	.	N	.	.	.	.	GT	./.
+NC_002945.4	30018	.	N	.	.	.	.	GT	./.
+NC_002945.4	30019	.	N	.	.	.	.	GT	./.
+NC_002945.4	30020	.	N	.	.	.	.	GT	./.
+NC_002945.4	30021	.	N	.	.	.	.	GT	./.
+NC_002945.4	30022	.	N	.	.	.	.	GT	./.
+NC_002945.4	30023	.	N	.	.	.	.	GT	./.
+NC_002945.4	30024	.	N	.	.	.	.	GT	./.
+NC_002945.4	30025	.	N	.	.	.	.	GT	./.
+NC_002945.4	30026	.	N	.	.	.	.	GT	./.
+NC_002945.4	30027	.	N	.	.	.	.	GT	./.
+NC_002945.4	30028	.	N	.	.	.	.	GT	./.
+NC_002945.4	30029	.	N	.	.	.	.	GT	./.
+NC_002945.4	30030	.	N	.	.	.	.	GT	./.
+NC_002945.4	30031	.	N	.	.	.	.	GT	./.
+NC_002945.4	30032	.	N	.	.	.	.	GT	./.
+NC_002945.4	30033	.	N	.	.	.	.	GT	./.
+NC_002945.4	30034	.	N	.	.	.	.	GT	./.
+NC_002945.4	30035	.	N	.	.	.	.	GT	./.
+NC_002945.4	30036	.	N	.	.	.	.	GT	./.
+NC_002945.4	30037	.	N	.	.	.	.	GT	./.
+NC_002945.4	30038	.	N	.	.	.	.	GT	./.
+NC_002945.4	30039	.	N	.	.	.	.	GT	./.
+NC_002945.4	30040	.	N	.	.	.	.	GT	./.
+NC_002945.4	30041	.	N	.	.	.	.	GT	./.
+NC_002945.4	30042	.	N	.	.	.	.	GT	./.
+NC_002945.4	30043	.	N	.	.	.	.	GT	./.
+NC_002945.4	30044	.	N	.	.	.	.	GT	./.
+NC_002945.4	30045	.	N	.	.	.	.	GT	./.
+NC_002945.4	30046	.	N	.	.	.	.	GT	./.
+NC_002945.4	30047	.	N	.	.	.	.	GT	./.
+NC_002945.4	30048	.	N	.	.	.	.	GT	./.
+NC_002945.4	30049	.	N	.	.	.	.	GT	./.
+NC_002945.4	30050	.	N	.	.	.	.	GT	./.
+NC_002945.4	30051	.	N	.	.	.	.	GT	./.
+NC_002945.4	30052	.	N	.	.	.	.	GT	./.
+NC_002945.4	30053	.	N	.	.	.	.	GT	./.
+NC_002945.4	30054	.	N	.	.	.	.	GT	./.
+NC_002945.4	30055	.	N	.	.	.	.	GT	./.
+NC_002945.4	30056	.	N	.	.	.	.	GT	./.
+NC_002945.4	30057	.	N	.	.	.	.	GT	./.
+NC_002945.4	30058	.	N	.	.	.	.	GT	./.
+NC_002945.4	30059	.	N	.	.	.	.	GT	./.
+NC_002945.4	30060	.	N	.	.	.	.	GT	./.
+NC_002945.4	30061	.	N	.	.	.	.	GT	./.
+NC_002945.4	30062	.	N	.	.	.	.	GT	./.
+NC_002945.4	30063	.	N	.	.	.	.	GT	./.
+NC_002945.4	30064	.	N	.	.	.	.	GT	./.
+NC_002945.4	30065	.	N	.	.	.	.	GT	./.
+NC_002945.4	30066	.	N	.	.	.	.	GT	./.
+NC_002945.4	30067	.	N	.	.	.	.	GT	./.
+NC_002945.4	30068	.	N	.	.	.	.	GT	./.
+NC_002945.4	30069	.	N	.	.	.	.	GT	./.
+NC_002945.4	30070	.	N	.	.	.	.	GT	./.
+NC_002945.4	30071	.	N	.	.	.	.	GT	./.
+NC_002945.4	30072	.	N	.	.	.	.	GT	./.
+NC_002945.4	30073	.	N	.	.	.	.	GT	./.
+NC_002945.4	30074	.	N	.	.	.	.	GT	./.
+NC_002945.4	30075	.	N	.	.	.	.	GT	./.
+NC_002945.4	30076	.	N	.	.	.	.	GT	./.
+NC_002945.4	30077	.	N	.	.	.	.	GT	./.
+NC_002945.4	30078	.	N	.	.	.	.	GT	./.
+NC_002945.4	30079	.	N	.	.	.	.	GT	./.
+NC_002945.4	30080	.	N	.	.	.	.	GT	./.
+NC_002945.4	30081	.	N	.	.	.	.	GT	./.
+NC_002945.4	30082	.	N	.	.	.	.	GT	./.
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+NC_002945.4	151040	.	N	.	.	.	.	GT	./.
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+NC_002945.4	306656	.	N	.	.	.	.	GT	./.
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+NC_002945.4	306658	.	N	.	.	.	.	GT	./.
+NC_002945.4	306659	.	N	.	.	.	.	GT	./.
+NC_002945.4	306660	.	N	.	.	.	.	GT	./.
+NC_002945.4	306661	.	N	.	.	.	.	GT	./.
+NC_002945.4	306662	.	N	.	.	.	.	GT	./.
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+NC_002945.4	306664	.	N	.	.	.	.	GT	./.
+NC_002945.4	306665	.	N	.	.	.	.	GT	./.
+NC_002945.4	306666	.	N	.	.	.	.	GT	./.
+NC_002945.4	306667	.	N	.	.	.	.	GT	./.
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+NC_002945.4	306670	.	N	.	.	.	.	GT	./.
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+NC_002945.4	306672	.	N	.	.	.	.	GT	./.
+NC_002945.4	306673	.	N	.	.	.	.	GT	./.
+NC_002945.4	306674	.	N	.	.	.	.	GT	./.
+NC_002945.4	306675	.	N	.	.	.	.	GT	./.
+NC_002945.4	306676	.	N	.	.	.	.	GT	./.
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+NC_002945.4	332124	.	C	T	235.47099999999998	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=10;CIGAR=1X;DP=11;DPB=11;DPRA=0;EPP=6.48466;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=59.1;MQMR=0;NS=1;NUMALT=1;ODDS=18.4681;PAIRED=0.9;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=314;QR=0;RO=0;RPL=10;RPP=24.725;RPPR=0;RPR=0;RUN=1;SAF=7;SAP=6.48466;SAR=3;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:11:0,10:0:0:10:314:-28.4197,-3.0103,0
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+NC_002945.4	332160	.	N	.	.	.	.	GT	./.
+NC_002945.4	332161	.	N	.	.	.	.	GT	./.
+NC_002945.4	332162	.	N	.	.	.	.	GT	./.
+NC_002945.4	332163	.	N	.	.	.	.	GT	./.
+NC_002945.4	332164	.	N	.	.	.	.	GT	./.
+NC_002945.4	332165	.	N	.	.	.	.	GT	./.
+NC_002945.4	332166	.	N	.	.	.	.	GT	./.
+NC_002945.4	332167	.	N	.	.	.	.	GT	./.
+NC_002945.4	332168	.	N	.	.	.	.	GT	./.
+NC_002945.4	332169	.	N	.	.	.	.	GT	./.
+NC_002945.4	332170	.	N	.	.	.	.	GT	./.
+NC_002945.4	332171	.	N	.	.	.	.	GT	./.
+NC_002945.4	332172	.	N	.	.	.	.	GT	./.
+NC_002945.4	332173	.	N	.	.	.	.	GT	./.
+NC_002945.4	332174	.	N	.	.	.	.	GT	./.
+NC_002945.4	332175	.	N	.	.	.	.	GT	./.
+NC_002945.4	332176	.	N	.	.	.	.	GT	./.
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+NC_002945.4	332192	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333486	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333488	.	N	.	.	.	.	GT	./.
+NC_002945.4	333489	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333491	.	N	.	.	.	.	GT	./.
+NC_002945.4	333492	.	N	.	.	.	.	GT	./.
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+NC_002945.4	333633	.	N	.	.	.	.	GT	./.
+NC_002945.4	333634	.	N	.	.	.	.	GT	./.
+NC_002945.4	334320	.	T	C	2194.66	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=79;CIGAR=1X;DP=80;DPB=80;DPRA=0;EPP=3.69747;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=53.4051;MQMR=0;NS=1;NUMALT=1;ODDS=114.122;PAIRED=0.987342;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=2577;QR=0;RO=0;RPL=41;RPP=3.25768;RPPR=0;RPR=38;RUN=1;SAF=46;SAP=7.6556;SAR=33;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:80:0,79:0:0:79:2577:-223.164,-23.7814,0
+NC_002945.4	334323	.	T	C	2171.15	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=79;CIGAR=1X;DP=79;DPB=79;DPRA=0;EPP=5.23675;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=53.4051;MQMR=0;NS=1;NUMALT=1;ODDS=114.122;PAIRED=0.987342;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=2540;QR=0;RO=0;RPL=40;RPP=3.03779;RPPR=0;RPR=39;RUN=1;SAF=45;SAP=6.33623;SAR=34;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:79:0,79:0:0:79:2540:-220.812,-23.7814,0
+NC_002945.4	336477	.	N	.	.	.	.	GT	./.
+NC_002945.4	336478	.	N	.	.	.	.	GT	./.
+NC_002945.4	336479	.	N	.	.	.	.	GT	./.
+NC_002945.4	336480	.	N	.	.	.	.	GT	./.
+NC_002945.4	336481	.	N	.	.	.	.	GT	./.
+NC_002945.4	336482	.	N	.	.	.	.	GT	./.
+NC_002945.4	336483	.	N	.	.	.	.	GT	./.
+NC_002945.4	336484	.	N	.	.	.	.	GT	./.
+NC_002945.4	336485	.	N	.	.	.	.	GT	./.
+NC_002945.4	336486	.	N	.	.	.	.	GT	./.
+NC_002945.4	336487	.	N	.	.	.	.	GT	./.
+NC_002945.4	336488	.	N	.	.	.	.	GT	./.
+NC_002945.4	336489	.	N	.	.	.	.	GT	./.
+NC_002945.4	336590	.	N	.	.	.	.	GT	./.
+NC_002945.4	336591	.	N	.	.	.	.	GT	./.
+NC_002945.4	336592	.	N	.	.	.	.	GT	./.
+NC_002945.4	336593	.	N	.	.	.	.	GT	./.
+NC_002945.4	336594	.	N	.	.	.	.	GT	./.
+NC_002945.4	336595	.	N	.	.	.	.	GT	./.
+NC_002945.4	336596	.	N	.	.	.	.	GT	./.
+NC_002945.4	336597	.	N	.	.	.	.	GT	./.
+NC_002945.4	336598	.	N	.	.	.	.	GT	./.
+NC_002945.4	336599	.	N	.	.	.	.	GT	./.
+NC_002945.4	336600	.	N	.	.	.	.	GT	./.
+NC_002945.4	336601	.	N	.	.	.	.	GT	./.
+NC_002945.4	336602	.	N	.	.	.	.	GT	./.
+NC_002945.4	336603	.	N	.	.	.	.	GT	./.
+NC_002945.4	336604	.	N	.	.	.	.	GT	./.
+NC_002945.4	336605	.	N	.	.	.	.	GT	./.
+NC_002945.4	336606	.	N	.	.	.	.	GT	./.
+NC_002945.4	336607	.	N	.	.	.	.	GT	./.
+NC_002945.4	336608	.	N	.	.	.	.	GT	./.
+NC_002945.4	336609	.	N	.	.	.	.	GT	./.
+NC_002945.4	336610	.	N	.	.	.	.	GT	./.
+NC_002945.4	336611	.	N	.	.	.	.	GT	./.
+NC_002945.4	336612	.	N	.	.	.	.	GT	./.
+NC_002945.4	336613	.	N	.	.	.	.	GT	./.
+NC_002945.4	336614	.	N	.	.	.	.	GT	./.
+NC_002945.4	336615	.	N	.	.	.	.	GT	./.
+NC_002945.4	336616	.	N	.	.	.	.	GT	./.
+NC_002945.4	336617	.	N	.	.	.	.	GT	./.
+NC_002945.4	336618	.	N	.	.	.	.	GT	./.
+NC_002945.4	336619	.	N	.	.	.	.	GT	./.
+NC_002945.4	336620	.	N	.	.	.	.	GT	./.
+NC_002945.4	336621	.	N	.	.	.	.	GT	./.
+NC_002945.4	336622	.	N	.	.	.	.	GT	./.
+NC_002945.4	336623	.	N	.	.	.	.	GT	./.
+NC_002945.4	336624	.	N	.	.	.	.	GT	./.
+NC_002945.4	336625	.	N	.	.	.	.	GT	./.
+NC_002945.4	336626	.	N	.	.	.	.	GT	./.
+NC_002945.4	336627	.	N	.	.	.	.	GT	./.
+NC_002945.4	336628	.	N	.	.	.	.	GT	./.
+NC_002945.4	336629	.	N	.	.	.	.	GT	./.
+NC_002945.4	336630	.	N	.	.	.	.	GT	./.
+NC_002945.4	336631	.	N	.	.	.	.	GT	./.
+NC_002945.4	336632	.	N	.	.	.	.	GT	./.
+NC_002945.4	336633	.	N	.	.	.	.	GT	./.
+NC_002945.4	336634	.	N	.	.	.	.	GT	./.
+NC_002945.4	336635	.	N	.	.	.	.	GT	./.
+NC_002945.4	336636	.	N	.	.	.	.	GT	./.
+NC_002945.4	336637	.	N	.	.	.	.	GT	./.
+NC_002945.4	336638	.	N	.	.	.	.	GT	./.
+NC_002945.4	336639	.	N	.	.	.	.	GT	./.
+NC_002945.4	339369	.	N	.	.	.	.	GT	./.
+NC_002945.4	339370	.	N	.	.	.	.	GT	./.
+NC_002945.4	339371	.	N	.	.	.	.	GT	./.
+NC_002945.4	339372	.	N	.	.	.	.	GT	./.
+NC_002945.4	339373	.	N	.	.	.	.	GT	./.
+NC_002945.4	339374	.	N	.	.	.	.	GT	./.
+NC_002945.4	339375	.	N	.	.	.	.	GT	./.
+NC_002945.4	339376	.	N	.	.	.	.	GT	./.
+NC_002945.4	339377	.	N	.	.	.	.	GT	./.
+NC_002945.4	339378	.	N	.	.	.	.	GT	./.
+NC_002945.4	339379	.	N	.	.	.	.	GT	./.
+NC_002945.4	339380	.	N	.	.	.	.	GT	./.
+NC_002945.4	339381	.	N	.	.	.	.	GT	./.
+NC_002945.4	339382	.	N	.	.	.	.	GT	./.
+NC_002945.4	339383	.	N	.	.	.	.	GT	./.
+NC_002945.4	339384	.	N	.	.	.	.	GT	./.
+NC_002945.4	339385	.	N	.	.	.	.	GT	./.
+NC_002945.4	339386	.	N	.	.	.	.	GT	./.
+NC_002945.4	339387	.	N	.	.	.	.	GT	./.
+NC_002945.4	339388	.	N	.	.	.	.	GT	./.
+NC_002945.4	339389	.	N	.	.	.	.	GT	./.
+NC_002945.4	339390	.	N	.	.	.	.	GT	./.
+NC_002945.4	339391	.	N	.	.	.	.	GT	./.
+NC_002945.4	339392	.	N	.	.	.	.	GT	./.
+NC_002945.4	339393	.	N	.	.	.	.	GT	./.
+NC_002945.4	339394	.	N	.	.	.	.	GT	./.
+NC_002945.4	339395	.	N	.	.	.	.	GT	./.
+NC_002945.4	339396	.	N	.	.	.	.	GT	./.
+NC_002945.4	339397	.	N	.	.	.	.	GT	./.
+NC_002945.4	339398	.	N	.	.	.	.	GT	./.
+NC_002945.4	339399	.	N	.	.	.	.	GT	./.
+NC_002945.4	339400	.	N	.	.	.	.	GT	./.
+NC_002945.4	339401	.	N	.	.	.	.	GT	./.
+NC_002945.4	339402	.	N	.	.	.	.	GT	./.
+NC_002945.4	339403	.	N	.	.	.	.	GT	./.
+NC_002945.4	339404	.	N	.	.	.	.	GT	./.
+NC_002945.4	339405	.	N	.	.	.	.	GT	./.
+NC_002945.4	339406	.	N	.	.	.	.	GT	./.
+NC_002945.4	339407	.	N	.	.	.	.	GT	./.
+NC_002945.4	339408	.	N	.	.	.	.	GT	./.
+NC_002945.4	339409	.	N	.	.	.	.	GT	./.
+NC_002945.4	339410	.	N	.	.	.	.	GT	./.
+NC_002945.4	339411	.	N	.	.	.	.	GT	./.
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+NC_002945.4	452398	.	G	A	5682.95	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=191;CIGAR=1X;DP=193;DPB=193;DPRA=0;EPP=8.02401;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=269.387;PAIRED=0.994764;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=6375;QR=0;RO=0;RPL=108;RPP=10.1159;RPPR=0;RPR=83;RUN=1;SAF=86;SAP=7.1145;SAR=105;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:193:0,191:0:0:191:6375:-573.63,-57.4967,0
+NC_002945.4	460722	.	G	A	4946.91	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=165;CIGAR=1X;DP=166;DPB=166;DPRA=0;EPP=11.2356;EPPR=5.18177;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=225.021;PAIRED=0.981818;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=5569;QR=29;RO=1;RPL=87;RPP=4.0763;RPPR=5.18177;RPR=78;RUN=1;SAF=85;SAP=3.33931;SAR=80;SRF=0;SRP=5.18177;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:166:1,165:1:29:165:5569:-498.37,-47.0713,0
+NC_002945.4	467343	.	C	T	4694.23	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=159;CIGAR=1X;DP=163;DPB=163;DPRA=0;EPP=5.31834;EPPR=5.18177;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=220.934;PAIRED=0.981132;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=5264;QR=12;RO=1;RPL=80;RPP=3.02396;RPPR=5.18177;RPR=79;RUN=1;SAF=72;SAP=6.08314;SAR=87;SRF=1;SRP=5.18177;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:163:1,159:1:12:159:5264:-472.655,-47.0865,0
+NC_002945.4	467402	.	C	A	5465.13	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=182;CIGAR=1X;DP=183;DPB=183;DPRA=0;EPP=3.43982;EPPR=5.18177;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=249.181;PAIRED=0.978022;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=6135;QR=26;RO=1;RPL=87;RPP=3.77389;RPPR=5.18177;RPR=95;RUN=1;SAF=85;SAP=4.72839;SAR=97;SRF=1;SRP=5.18177;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:183:1,182:1:26:182:6135:-549.586,-52.4887,0
+NC_002945.4	479644	.	G	A	6502.05	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=213;CIGAR=1X;DP=213;DPB=213;DPRA=0;EPP=3.50984;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=299.886;PAIRED=0.971831;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7282;QR=0;RO=0;RPL=118;RPP=8.4033;RPPR=0;RPR=95;RUN=1;SAF=93;SAP=10.4422;SAR=120;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:213:0,213:0:0:213:7282:-655.323,-64.1194,0
+NC_002945.4	483845	.	T	C	6908.05	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=226;CIGAR=1X;DP=226;DPB=226;DPRA=0;EPP=4.39389;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=59.6947;MQMR=0;NS=1;NUMALT=1;ODDS=317.908;PAIRED=0.986726;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7736;QR=0;RO=0;RPL=115;RPP=3.16403;RPPR=0;RPR=111;RUN=1;SAF=110;SAP=3.3562;SAR=116;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:226:0,226:0:0:226:7736:-694.819,-68.0328,0
+NC_002945.4	485584	.	G	A	6925.43	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=219;CIGAR=1X;DP=219;DPB=219;DPRA=0;EPP=3.09954;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=308.204;PAIRED=0.986301;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7743;QR=0;RO=0;RPL=119;RPP=6.58976;RPPR=0;RPR=100;RUN=1;SAF=113;SAP=3.49615;SAR=106;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:219:0,219:0:0:219:7743:-696.763,-65.9256,0
+NC_002945.4	488897	.	G	T	3635.93	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=139;CIGAR=1X;DP=147;DPB=147;DPRA=0;EPP=3.1509;EPPR=10.7656;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=165.544;PAIRED=0.985612;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=4207;QR=110;RO=7;RPL=43;RPP=46.8928;RPPR=5.80219;RPR=96;RUN=1;SAF=78;SAP=7.52509;SAR=61;SRF=6;SRP=10.7656;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:147:7,139:7:110:139:4207:-368.725,-34.0199,0
+NC_002945.4	490878	.	G	A	7054.95	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=222;CIGAR=1X;DP=223;DPB=223;DPRA=0;EPP=5.51434;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=312.363;PAIRED=0.977477;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7893;QR=0;RO=0;RPL=99;RPP=8.64439;RPPR=0;RPR=123;RUN=1;SAF=108;SAP=3.36243;SAR=114;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:223:0,222:0:0:222:7893:-710.157,-66.8287,0
+NC_002945.4	507929	.	T	C	5517.08	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=179;CIGAR=1X;DP=179;DPB=179;DPRA=0;EPP=3.02243;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=252.752;PAIRED=0.977654;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=6172;QR=0;RO=0;RPL=86;RPP=3.60473;RPPR=0;RPR=93;RUN=1;SAF=92;SAP=3.31358;SAR=87;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:179:0,179:0:0:179:6172:-555.473,-53.8844,0
+NC_002945.4	518522	.	C	T	5022.35	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=170;CIGAR=1X;DP=175;DPB=175;DPRA=0;EPP=3.8278;EPPR=9.52472;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=60;NS=1;NUMALT=1;ODDS=222.502;PAIRED=0.994118;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=5690;QR=59;RO=3;RPL=64;RPP=25.5425;RPPR=3.73412;RPR=106;RUN=1;SAF=91;SAP=4.84966;SAR=79;SRF=2;SRP=3.73412;SRR=1;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:175:3,170:3:59:170:5690:-506.649,-46.7265,0
+NC_002945.4	519412	.	T	C	2988.47	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=100;CIGAR=1X;DP=100;DPB=100;DPRA=0;EPP=4.40004;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=143.235;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=3388;QR=0;RO=0;RPL=34;RPP=25.2462;RPPR=0;RPR=66;RUN=1;SAF=58;SAP=8.56927;SAR=42;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:100:0,100:0:0:100:3388:-305.075,-30.103,0
+NC_002945.4	541571	.	T	C	4690.54	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=154;CIGAR=1X;DP=154;DPB=154;DPRA=0;EPP=15.7007;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=218.095;PAIRED=0.993506;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=5283;QR=0;RO=0;RPL=60;RPP=19.3104;RPPR=0;RPR=94;RUN=1;SAF=78;SAP=3.0667;SAR=76;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:154:0,154:0:0:154:5283:-475.539,-46.3586,0
+NC_002945.4	544180	.	C	T	6381.36	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=214;CIGAR=1X;DP=218;DPB=218;DPRA=0;EPP=4.02501;EPPR=0;GTI=0;LEN=1;MEANALT=3;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=301.272;PAIRED=0.990654;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7162;QR=0;RO=0;RPL=131;RPP=26.3891;RPPR=0;RPR=83;RUN=1;SAF=103;SAP=3.65971;SAR=111;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:218:0,214:0:0:214:7162:-644.439,-64.4204,0
+NC_002945.4	577068	.	G	T	3066.54	.	AB=0.881481;ABP=173.656;AC=1;AF=0.5;AN=2;AO=119;CIGAR=1X;DP=135;DPB=135;DPRA=0;EPP=9.59771;EPPR=4.31318;GTI=0;LEN=1;MEANALT=2;MQ=59.8487;MQMR=60;NS=1;NUMALT=1;ODDS=61.7924;PAIRED=0.991597;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=3865;QR=471;RO=15;RPL=63;RPP=3.90444;RPPR=35.5824;RPR=56;RUN=1;SAF=50;SAP=9.59771;SAR=69;SRF=9;SRP=4.31318;SRR=6;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	0/1:135:15,119:15:471:119:3865:-307.53,0,-2.2127
+NC_002945.4	598704	.	C	G	6668.19	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=222;CIGAR=1X;DP=222;DPB=222;DPRA=0;EPP=27.4638;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=312.363;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7554;QR=0;RO=0;RPL=70;RPP=68.7805;RPPR=0;RPR=152;RUN=1;SAF=112;SAP=3.04943;SAR=110;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:222:0,222:0:0:222:7554:-679.797,-66.8287,0
+NC_002945.4	600207	.	T	C	6781.53	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=217;CIGAR=1X;DP=217;DPB=217;DPRA=0;EPP=8.30389;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQ=59.9724;MQMR=0;NS=1;NUMALT=1;ODDS=305.431;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=7591;QR=0;RO=0;RPL=96;RPP=9.26454;RPPR=0;RPR=121;RUN=1;SAF=110;SAP=3.10036;SAR=107;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:217:0,217:0:0:217:7591:-683.114,-65.3235,0
+NC_002945.4	608835	.	T	C	209.35299999999998	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=11;CIGAR=1X;DP=12;DPB=12;DPRA=0;EPP=19.0002;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=34.8182;MQMR=0;NS=1;NUMALT=1;ODDS=19.8544;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=377;QR=0;RO=0;RPL=1;RPP=19.0002;RPPR=0;RPR=10;RUN=1;SAF=11;SAP=26.8965;SAR=0;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:12:0,11:0:0:11:377:-28.7865,-3.31133,0
+NC_002945.4	611077	.	A	G	6633.15	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=225;CIGAR=1X;DP=230;DPB=230;DPRA=0;EPP=3.4832;EPPR=7.35324;GTI=0;LEN=1;MEANALT=3;MQ=59.96;MQMR=60;NS=1;NUMALT=1;ODDS=308.327;PAIRED=0.991111;PAIREDR=1;PAO=0;PQA=0;PQR=0;PRO=0;QA=7440;QR=24;RO=2;RPL=100;RPP=9.04217;RPPR=7.35324;RPR=125;RUN=1;SAF=131;SAP=16.2225;SAR=94;SRF=0;SRP=7.35324;SRR=2;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:230:2,225:2:24:225:7440:-667.303,-66.1738,0
+NC_002945.4	622386	.	C	G	6094.46	.	AB=0;ABP=0;AC=2;AF=1;AN=2;AO=199;CIGAR=1X;DP=200;DPB=200;DPRA=0;EPP=3.89417;EPPR=0;GTI=0;LEN=1;MEANALT=2;MQ=60;MQMR=0;NS=1;NUMALT=1;ODDS=280.478;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=6828;QR=0;RO=0;RPL=90;RPP=6.9495;RPPR=0;RPR=109;RUN=1;SAF=112;SAP=9.83025;SAR=87;SRF=0;SRP=0;SRR=0;TYPE=snp;technology.ILLUMINA=1	GT:DP:AD:RO:QR:AO:QA:GL	1/1:200:0,199:0:0:199:6828:-614.351,-59.905,0
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/json_all_vcf.json	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,1 @@
+{"columns":[
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/json_avg_mq_all_vcf.json	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,1 @@
+{"name":null,"index":[
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_fasta.fasta	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,4 @@
+>SRR1792272_zc
+>SRR8073662_zc
+>input_zc_vcf_vcf
+>root
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_json_avg_mq.json	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,1 @@
+{"name":null,"index":["NC_002945
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_json_snps.json	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,1 @@
+{"columns":["NC_002945
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/output_summary.html	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,6 @@
+<html>
+<head></head>
+<br/><b>Number of VCF inputs:</b> 3<br/><b>Reference:</b>
+<br/><b>Total run time:</b>
+</body>
+</html>
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/tool-data/vsnp_excel.loc.sample	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,4 @@
+## vSNP Excel files
+#Value	Name	Path	Description
+#AF2122	Mbovis_define_filter.xlsx	vsnp/AF2122/Mbovis_define_filter.xlsx	Excel file for Mycobacterium bovis AF2122/97
+#NC_006932	Bab1_define_filter.xlsx	/vsnp/NC_006932/Bab1_define_filter.xlsx	Excel file for Brucella abortus bv. 1 str. 9-941
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/tool_data_table_conf.xml.sample	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,7 @@
+<tables>
+    <table name="vsnp_excel" comment_char="#">
+        <columns>value, name, path, description</columns>
+        <file path="tool-data/vsnp_excel.loc" />
+    </table>
+</tables>
+
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/vsnp_get_snps.py	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,519 @@
+#!/usr/bin/env python
+
+# Collect quality parsimonious SNPs from vcf files and output alignment files in fasta format.
+
+import argparse
+import multiprocessing
+import os
+import pandas
+import queue
+import shutil
+import sys
+import time
+import vcf
+from collections import OrderedDict
+from datetime import datetime
+
+ALL_VCFS_DIR = 'all_vcf'
+INPUT_VCF_DIR = 'input_vcf_dir'
+OUTPUT_JSON_AVG_MQ_DIR = 'output_json_avg_mq_dir'
+OUTPUT_JSON_SNPS_DIR = 'output_json_snps_dir'
+OUTPUT_SNPS_DIR = 'output_snps_dir'
+
+
+def get_time_stamp():
+    return datetime.fromtimestamp(time.time()).strftime('%Y-%m-%d %H-%M-%S')
+
+
+def set_num_cpus(num_files, processes):
+    num_cpus = int(multiprocessing.cpu_count())
+    if num_files < num_cpus and num_files < processes:
+        return num_files
+    if num_cpus < processes:
+        half_cpus = int(num_cpus / 2)
+        if num_files < half_cpus:
+            return num_files
+        return half_cpus
+    return processes
+
+
+def setup_all_vcfs(vcf_files, vcf_dirs):
+    # Create the all_vcfs directory and link
+    # all input vcf files into it for processing.
+    os.makedirs(ALL_VCFS_DIR)
+    vcf_dirs.append(ALL_VCFS_DIR)
+    for vcf_file in vcf_files:
+        file_name_base = os.path.basename(vcf_file)
+        dst_file = os.path.join(ALL_VCFS_DIR, file_name_base)
+        os.symlink(vcf_file, dst_file)
+    return vcf_dirs
+
+
+class SnpFinder:
+
+    def __init__(self, num_files, reference, excel_grouper_file,
+                 all_isolates, ac, mq_val, n_threshold, qual_threshold, output_summary):
+        self.ac = ac
+        self.all_isolates = all_isolates
+        self.all_positions = None
+        # Filter based on the contents of an Excel file.
+        self.excel_grouper_file = excel_grouper_file
+        # Use Genbank file
+        self.groups = []
+        # This will be populated from the columns
+        # in the Excel filter file if it is used.
+        self.mq_val = mq_val
+        self.n_threshold = n_threshold
+        self.qual_threshold = qual_threshold
+        self.reference = reference
+        self.start_time = get_time_stamp()
+        self.summary_str = ""
+        self.timer_start = datetime.now()
+        self.num_files = num_files
+        self.initiate_summary(output_summary)
+
+    def append_to_summary(self, html_str):
+        self.summary_str = "%s%s" % (self.summary_str, html_str)
+
+    def bin_input_files(self, filename, samples_groups_dict, defining_snps, inverted_defining_snps, found_positions, found_positions_mix):
+        sample_groups_list = []
+        table_name = self.get_base_file_name(filename)
+        try:
+            defining_snp = False
+            # Absolute positions in set union of two lists.
+            for abs_position in list(defining_snps.keys() & (found_positions.keys() | found_positions_mix.keys())):
+                group = defining_snps[abs_position]
+                sample_groups_list.append(group)
+                self.check_add_group(group)
+                if len(list(defining_snps.keys() & found_positions_mix.keys())) > 0:
+                    table_name = self.get_base_file_name(filename)
+                    table_name = '%s<font color="red">[[MIXED]]</font>' % table_name
+                self.copy_file(filename, group)
+                defining_snp = True
+            if not set(inverted_defining_snps.keys()).intersection(found_positions.keys() | found_positions_mix.keys()):
+                for abs_position in list(inverted_defining_snps.keys()):
+                    group = inverted_defining_snps[abs_position]
+                    sample_groups_list.append(group)
+                    self.check_add_group(group)
+                    self.copy_file(filename, group)
+                    defining_snp = True
+            if defining_snp:
+                samples_groups_dict[table_name] = sorted(sample_groups_list)
+            else:
+                samples_groups_dict[table_name] = ['<font color="red">No defining SNP</font>']
+        except TypeError as e:
+            msg = "<br/>Error processing file %s to generate samples_groups_dict: %s<br/>" % (filename, str(e))
+            self.append_to_summary(msg)
+            samples_groups_dict[table_name] = [msg]
+        return samples_groups_dict
+
+    def check_add_group(self, group):
+        if group not in self.groups:
+            self.groups.append(group)
+
+    def copy_file(self, filename, dir):
+        if not os.path.exists(dir):
+            os.makedirs(dir)
+        shutil.copy(filename, dir)
+
+    def decide_snps(self, filename):
+        positions_dict = self.all_positions
+        # Find the SNPs in a vcf file to produce a pandas data
+        # frame and a dictionary containing sample map qualities.
+        sample_map_qualities = {}
+        # Eliminate the path.
+        file_name_base = self.get_base_file_name(filename)
+        vcf_reader = vcf.Reader(open(filename, 'r'))
+        sample_dict = {}
+        for record in vcf_reader:
+            alt = str(record.ALT[0])
+            record_position = "%s:%s" % (str(record.CHROM), str(record.POS))
+            if record_position in positions_dict:
+                if alt == "None":
+                    sample_dict.update({record_position: "-"})
+                else:
+                    # Not sure this is the best place to capture MQM average
+                    # may be faster after parsimony SNPs are decided, but
+                    # then it will require opening the files again.
+                    # On rare occassions MQM gets called "NaN", thus passing
+                    # a string when a number is expected when calculating average.
+                    mq_val = self.get_mq_val(record.INFO, filename)
+                    if str(mq_val).lower() not in ["nan"]:
+                        sample_map_qualities.update({record_position: mq_val})
+                    # Add parameters here to change what each vcf represents.
+                    # SNP is represented in table, now how will the vcf represent
+                    # the called position alt != "None", which means a deletion
+                    # as alt is not record.FILTER, or rather passed.
+                    len_alt = len(alt)
+                    if len_alt == 1:
+                        qual_val = self.val_as_int(record.QUAL)
+                        ac = record.INFO['AC'][0]
+                        ref = str(record.REF[0])
+                        if ac == 2 and qual_val > self.n_threshold:
+                            sample_dict.update({record_position: alt})
+                        elif ac == 1 and qual_val > self.n_threshold:
+                            alt_ref = "%s%s" % (alt, ref)
+                            if alt_ref == "AG":
+                                sample_dict.update({record_position: "R"})
+                            elif alt_ref == "CT":
+                                sample_dict.update({record_position: "Y"})
+                            elif alt_ref == "GC":
+                                sample_dict.update({record_position: "S"})
+                            elif alt_ref == "AT":
+                                sample_dict.update({record_position: "W"})
+                            elif alt_ref == "GT":
+                                sample_dict.update({record_position: "K"})
+                            elif alt_ref == "AC":
+                                sample_dict.update({record_position: "M"})
+                            elif alt_ref == "GA":
+                                sample_dict.update({record_position: "R"})
+                            elif alt_ref == "TC":
+                                sample_dict.update({record_position: "Y"})
+                            elif alt_ref == "CG":
+                                sample_dict.update({record_position: "S"})
+                            elif alt_ref == "TA":
+                                sample_dict.update({record_position: "W"})
+                            elif alt_ref == "TG":
+                                sample_dict.update({record_position: "K"})
+                            elif alt_ref == "CA":
+                                sample_dict.update({record_position: "M"})
+                            else:
+                                sample_dict.update({record_position: "N"})
+                            # Poor calls
+                        elif qual_val <= 50:
+                            # Do not coerce record.REF[0] to a string!
+                            sample_dict.update({record_position: record.REF[0]})
+                        elif qual_val <= self.n_threshold:
+                            sample_dict.update({record_position: "N"})
+                        else:
+                            # Insurance -- Will still report on a possible
+                            # SNP even if missed with above statement
+                            # Do not coerce record.REF[0] to a string!
+                            sample_dict.update({record_position: record.REF[0]})
+        # Merge dictionaries and order
+        merge_dict = {}
+        # abs_pos:REF
+        merge_dict.update(positions_dict)
+        # abs_pos:ALT replacing all_positions, because keys must be unique
+        merge_dict.update(sample_dict)
+        sample_df = pandas.DataFrame(merge_dict, index=[file_name_base])
+        return sample_df, file_name_base, sample_map_qualities
+
+    def df_to_fasta(self, parsimonious_df, group):
+        # Generate SNP alignment file from the parsimonious_df
+        # data frame.
+        snps_file = os.path.join(OUTPUT_SNPS_DIR, "%s.fasta" % group)
+        test_duplicates = []
+        has_sequence_data = False
+        for index, row in parsimonious_df.iterrows():
+            for pos in row:
+                if len(pos) > 0:
+                    has_sequence_data = True
+                    break
+        if has_sequence_data:
+            with open(snps_file, 'w') as fh:
+                for index, row in parsimonious_df.iterrows():
+                    test_duplicates.append(row.name)
+                    if test_duplicates.count(row.name) < 2:
+                        print(f'>{row.name}', file=fh)
+                        for pos in row:
+                            print(pos, end='', file=fh)
+                        print("", file=fh)
+        return has_sequence_data
+
+    def find_initial_positions(self, filename):
+        # Find SNP positions in a vcf file.
+        found_positions = {}
+        found_positions_mix = {}
+        try:
+            vcf_reader = vcf.Reader(open(filename, 'r'))
+            try:
+                for record in vcf_reader:
+                    qual_val = self.val_as_int(record.QUAL)
+                    chrom = record.CHROM
+                    position = record.POS
+                    absolute_position = "%s:%s" % (str(chrom), str(position))
+                    alt = str(record.ALT[0])
+                    if alt != "None":
+                        mq_val = self.get_mq_val(record.INFO, filename)
+                        ac = record.INFO['AC'][0]
+                        len_ref = len(record.REF)
+                        if ac == self.ac and len_ref == 1 and qual_val > self.qual_threshold and mq_val > self.mq_val:
+                            found_positions.update({absolute_position: record.REF})
+                        if ac == 1 and len_ref == 1 and qual_val > self.qual_threshold and mq_val > self.mq_val:
+                            found_positions_mix.update({absolute_position: record.REF})
+                return found_positions, found_positions_mix
+            except (ZeroDivisionError, ValueError, UnboundLocalError, TypeError) as e:
+                self.append_to_summar("<br/>Error parsing record in file %s: %s<br/>" % (filename, str(e)))
+                return {'': ''}, {'': ''}
+        except (SyntaxError, AttributeError) as e:
+            self.append_to_summary("<br/>Error attempting to read file %s: %s<br/>" % (filename, str(e)))
+            return {'': ''}, {'': ''}
+
+    def gather_and_filter(self, prefilter_df, mq_averages, group_dir):
+        # Group a data frame of SNPs.
+        if self.excel_grouper_file is None:
+            filtered_all_df = prefilter_df
+            sheet_names = None
+        else:
+            # Filter positions to be removed from all.
+            xl = pandas.ExcelFile(self.excel_grouper_file)
+            sheet_names = xl.sheet_names
+            # Use the first column to filter "all" postions.
+            exclusion_list_all = self.get_position_list(sheet_names, 0)
+            exclusion_list_group = self.get_position_list(sheet_names, group_dir)
+            exclusion_list = exclusion_list_all + exclusion_list_group
+            # Filters for all applied.
+            filtered_all_df = prefilter_df.drop(columns=exclusion_list, errors='ignore')
+        json_snps_file = os.path.join(OUTPUT_JSON_SNPS_DIR, "%s.json" % group_dir)
+        parsimonious_df = self.get_parsimonious_df(filtered_all_df)
+        samples_number, columns = parsimonious_df.shape
+        if samples_number >= 4:
+            has_sequence_data = self.df_to_fasta(parsimonious_df, group_dir)
+            if has_sequence_data:
+                json_avg_mq_file = os.path.join(OUTPUT_JSON_AVG_MQ_DIR, "%s.json" % group_dir)
+                mq_averages.to_json(json_avg_mq_file, orient='split')
+                parsimonious_df.to_json(json_snps_file, orient='split')
+            else:
+                msg = "<br/>No sequence data"
+                if group_dir is not None:
+                    msg = "%s for group: %s" % (msg, group_dir)
+                self.append_to_summary("%s<br/>\n" % msg)
+        else:
+            msg = "<br/>Too few samples to build tree"
+            if group_dir is not None:
+                msg = "%s for group: %s" % (msg, group_dir)
+            self.append_to_summary("%s<br/>\n" % msg)
+
+    def get_base_file_name(self, file_path):
+        base_file_name = os.path.basename(file_path)
+        if base_file_name.find(".") > 0:
+            # Eliminate the extension.
+            return os.path.splitext(base_file_name)[0]
+        elif base_file_name.find("_") > 0:
+            # The dot extension was likely changed to
+            # the " character.
+            items = base_file_name.split("_")
+            return "_".join(items[0:-1])
+        else:
+            return base_file_name
+
+    def get_mq_val(self, record_info, filename):
+        # Get the MQ (gatk) or MQM (freebayes) value
+        # from the record.INFO component of the vcf file.
+        try:
+            mq_val = record_info['MQM']
+            return self.return_val(mq_val)
+        except Exception:
+            try:
+                mq_val = record_info['MQ']
+                return self.return_val(mq_val)
+            except Exception:
+                msg = "Invalid or unsupported vcf header %s in file: %s\n" % (str(record_info), filename)
+                sys.exit(msg)
+
+    def get_parsimonious_df(self, filtered_all_df):
+        # Get the parsimonious SNPs data frame
+        # from a data frame of filtered SNPs.
+        try:
+            ref_series = filtered_all_df.loc['root']
+            # In all_vcf root needs to be removed.
+            filtered_all_df = filtered_all_df.drop(['root'])
+        except KeyError:
+            pass
+        parsimony = filtered_all_df.loc[:, (filtered_all_df != filtered_all_df.iloc[0]).any()]
+        parsimony_positions = list(parsimony)
+        parse_df = filtered_all_df[parsimony_positions]
+        ref_df = ref_series.to_frame()
+        ref_df = ref_df.T
+        parsimonious_df = pandas.concat([parse_df, ref_df], join='inner')
+        return parsimonious_df
+
+    def get_position_list(self, sheet_names, group):
+        # Get a list of positions defined by an excel file.
+        exclusion_list = []
+        try:
+            filter_to_all = pandas.read_excel(self.excel_grouper_file, header=1, usecols=[group])
+            for value in filter_to_all.values:
+                value = str(value[0])
+                if "-" not in value.split(":")[-1]:
+                    exclusion_list.append(value)
+                elif "-" in value:
+                    try:
+                        chrom, sequence_range = value.split(":")
+                    except Exception as e:
+                        sys.exit(str(e))
+                    value = sequence_range.split("-")
+                    for position in range(int(value[0].replace(',', '')), int(value[1].replace(',', '')) + 1):
+                        exclusion_list.append(chrom + ":" + str(position))
+            return exclusion_list
+        except ValueError:
+            exclusion_list = []
+            return exclusion_list
+
+    def get_snps(self, task_queue, timeout):
+        while True:
+            try:
+                group_dir = task_queue.get(block=True, timeout=timeout)
+            except queue.Empty:
+                break
+            # Parse all vcf files to accumulate SNPs into a
+            # data frame.
+            positions_dict = {}
+            group_files = []
+            for file_name in os.listdir(os.path.abspath(group_dir)):
+                file_path = os.path.abspath(os.path.join(group_dir, file_name))
+                group_files.append(file_path)
+            for file_name in group_files:
+                try:
+                    found_positions, found_positions_mix = self.find_initial_positions(file_name)
+                    positions_dict.update(found_positions)
+                except Exception as e:
+                    self.append_to_summary("Error updating the positions_dict dictionary when processing file %s:\n%s\n" % (file_name, str(e)))
+            # Order before adding to file to match
+            # with ordering of individual samples.
+            # all_positions is abs_pos:REF
+            self.all_positions = OrderedDict(sorted(positions_dict.items()))
+            ref_positions_df = pandas.DataFrame(self.all_positions, index=['root'])
+            all_map_qualities = {}
+            df_list = []
+            for file_name in group_files:
+                sample_df, file_name_base, sample_map_qualities = self.decide_snps(file_name)
+                df_list.append(sample_df)
+                all_map_qualities.update({file_name_base: sample_map_qualities})
+            all_sample_df = pandas.concat(df_list)
+            # All positions have now been selected for each sample,
+            # so select parisomony informative SNPs.  This removes
+            # columns where all fields are the same.
+            # Add reference to top row.
+            prefilter_df = pandas.concat([ref_positions_df, all_sample_df], join='inner')
+            all_mq_df = pandas.DataFrame.from_dict(all_map_qualities)
+            mq_averages = all_mq_df.mean(axis=1).astype(int)
+            self.gather_and_filter(prefilter_df, mq_averages, group_dir)
+            task_queue.task_done()
+
+    def group_vcfs(self, vcf_files):
+        # Parse an excel file to produce a
+        # grouping dictionary for filtering SNPs.
+        xl = pandas.ExcelFile(self.excel_grouper_file)
+        sheet_names = xl.sheet_names
+        ws = pandas.read_excel(self.excel_grouper_file, sheet_name=sheet_names[0])
+        defining_snps = ws.iloc[0]
+        defsnp_iterator = iter(defining_snps.iteritems())
+        next(defsnp_iterator)
+        defining_snps = {}
+        inverted_defining_snps = {}
+        for abs_pos, group in defsnp_iterator:
+            if '!' in abs_pos:
+                inverted_defining_snps[abs_pos.replace('!', '')] = group
+            else:
+                defining_snps[abs_pos] = group
+        samples_groups_dict = {}
+        for vcf_file in vcf_files:
+            found_positions, found_positions_mix = self.find_initial_positions(vcf_file)
+            samples_groups_dict = self.bin_input_files(vcf_file, samples_groups_dict, defining_snps, inverted_defining_snps, found_positions, found_positions_mix)
+        # Output summary grouping table.
+        self.append_to_summary('<br/>')
+        self.append_to_summary('<b>Groupings with %d listed:</b><br/>\n' % len(samples_groups_dict))
+        self.append_to_summary('<table  cellpadding="5" cellspaging="5" border="1">\n')
+        for key, value in samples_groups_dict.items():
+            self.append_to_summary('<tr align="left"><th>Sample Name</th>\n')
+            self.append_to_summary('<td>%s</td>' % key)
+            for group in value:
+                self.append_to_summary('<td>%s</td>\n' % group)
+            self.append_to_summary('</tr>\n')
+        self.append_to_summary('</table><br/>\n')
+
+    def initiate_summary(self, output_summary):
+        # Output summary file handle.
+        self.append_to_summary('<html>\n')
+        self.append_to_summary('<head></head>\n')
+        self.append_to_summary('<body style=\"font-size:12px;">')
+        self.append_to_summary("<b>Time started:</b> %s<br/>" % str(get_time_stamp()))
+        self.append_to_summary("<b>Number of VCF inputs:</b> %d<br/>" % self.num_files)
+        self.append_to_summary("<b>Reference:</b> %s<br/>" % str(self.reference))
+        self.append_to_summary("<b>All isolates:</b> %s<br/>" % str(self.all_isolates))
+
+    def return_val(self, val, index=0):
+        # Handle element and single-element list values.
+        if isinstance(val, list):
+            return val[index]
+        return val
+
+    def val_as_int(self, val):
+        # Handle integer value conversion.
+        try:
+            return int(val)
+        except TypeError:
+            # val is likely None here.
+            return 0
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument('--all_isolates', action='store', dest='all_isolates', required=False, default="No", help='Create table with all isolates'),
+    parser.add_argument('--excel_grouper_file', action='store', dest='excel_grouper_file', required=False, default=None, help='Optional Excel filter file'),
+    parser.add_argument('--output_summary', action='store', dest='output_summary', help='Output summary html file'),
+    parser.add_argument('--reference', action='store', dest='reference', help='Reference file'),
+    parser.add_argument('--processes', action='store', dest='processes', type=int, help='User-selected number of processes to use for job splitting')
+
+    args = parser.parse_args()
+
+    # Initializations - TODO: should these be passed in as command line args?
+    ac = 2
+    mq_val = 56
+    n_threshold = 50
+    qual_threshold = 150
+
+    # Build the list of sample vcf files for the current run.
+    vcf_files = []
+    for file_name in os.listdir(INPUT_VCF_DIR):
+        file_path = os.path.abspath(os.path.join(INPUT_VCF_DIR, file_name))
+        vcf_files.append(file_path)
+
+    multiprocessing.set_start_method('spawn')
+    queue1 = multiprocessing.JoinableQueue()
+    num_files = len(vcf_files)
+    cpus = set_num_cpus(num_files, args.processes)
+    # Set a timeout for get()s in the queue.
+    timeout = 0.05
+
+    # Initialize the snp_finder object.
+    snp_finder = SnpFinder(num_files, args.reference, args.excel_grouper_file, args.all_isolates,
+                           ac, mq_val, n_threshold, qual_threshold, args.output_summary)
+
+    # Initialize the set of directories containiing vcf files for analysis.
+    vcf_dirs = []
+    if args.excel_grouper_file is None:
+        vcf_dirs = setup_all_vcfs(vcf_files, vcf_dirs)
+    else:
+        if args.all_isolates.lower() == "yes":
+            vcf_dirs = setup_all_vcfs(vcf_files, vcf_dirs)
+        # Parse the Excel file to detemine groups for filtering.
+        snp_finder.group_vcfs(vcf_files)
+        # Append the list of group directories created by
+        # the above call to the set of directories containing
+        # vcf files for analysis
+        group_dirs = [d for d in os.listdir(os.getcwd()) if os.path.isdir(d) and d in snp_finder.groups]
+        vcf_dirs.extend(group_dirs)
+
+    # Populate the queue for job splitting.
+    for vcf_dir in vcf_dirs:
+        queue1.put(vcf_dir)
+
+    # Complete the get_snps task.
+    processes = [multiprocessing.Process(target=snp_finder.get_snps, args=(queue1, timeout, )) for _ in range(cpus)]
+    for p in processes:
+        p.start()
+    for p in processes:
+        p.join()
+    queue1.join()
+
+    # Finish summary log.
+    snp_finder.append_to_summary("<br/><b>Time finished:</b> %s<br/>\n" % get_time_stamp())
+    total_run_time = datetime.now() - snp_finder.timer_start
+    snp_finder.append_to_summary("<br/><b>Total run time:</b> %s<br/>\n" % str(total_run_time))
+    snp_finder.append_to_summary('</body>\n</html>\n')
+    with open(args.output_summary, "w") as fh:
+        fh.write("%s" % snp_finder.summary_str)
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/vsnp_get_snps.xml	Tue Apr 21 10:14:11 2020 -0400
@@ -0,0 +1,179 @@
+<tool id="vsnp_get_snps" name="vSNP: get SNPs" version="1.0.0">
+    <description></description>
+    <requirements>
+        <requirement type="package" version="0.25.3">pandas</requirement>
+        <requirement type="package" version="0.6.8">pyvcf</requirement>
+        <requirement type="package" version="1.2.0">xlrd</requirement>
+    </requirements>
+    <command detect_errors="exit_code"><![CDATA[
+#import os
+#set input_vcf_dir = 'input_vcf_dir'
+#set input_zc_vcf_type = $input_zc_vcf_type_cond.input_zc_vcf_type
+#set output_json_avg_mq_dir = 'output_json_avg_mq_dir'
+#set output_json_snps_dir = 'output_json_snps_dir'
+#set output_snps_dir = 'output_snps_dir'
+mkdir -p $input_vcf_dir &&
+mkdir -p $output_json_avg_mq_dir &&
+mkdir -p $output_json_snps_dir &&
+mkdir -p $output_snps_dir &&
+#set reference = '?'
+#for $i in $input_vcf_collection:
+    #set reference = $i.metadata.dbkey
+    #set filename = $i.file_name
+    #set name = $i.name
+    ln -s $filename $input_vcf_dir/$name &&
+#end for
+#if str($input_zc_vcf_type) == "single":
+    #set input_zc_vcf = $input_zc_vcf_type_cond.input_zc_vcf
+    #set file_name_base = $os.path.basename($input_zc_vcf.file_name)
+    ln -s $input_zc_vcf $input_vcf_dir/$file_name_base &&
+#else
+    #for $i in $input_zc_vcf_type_cond.input_zc_vcf_collection:
+        #set filename = $i.file_name
+        #set name = $i.name
+        ln -s $filename $input_vcf_dir/$name &&
+    #end for
+#end if
+#if str($excel_grouper_cond.excel_grouper) == "yes":
+    #set excel_grouper_source = $excel_grouper_cond.excel_grouper_source_cond.excel_grouper_source
+    #if str($excel_grouper_source) == "cached":
+        #set excel_fields = $__app__.tool_data_tables['vsnp_excel'].get_fields()
+        #for $i in $excel_fields:
+            #if str($i[0]) == $reference:
+                #set excel_file = $i[2]
+                #break
+            #end if
+        #end for
+    #else:
+        #set excel_file = $excel_grouper_cond.excel_grouper_source_cond.excel_grouper_file
+    #end if
+#end if
+python '$__tool_directory__/vsnp_get_snps.py'
+--processes $processes
+--reference '$reference'
+#if str($excel_grouper_cond.excel_grouper) == "yes":
+    --excel_grouper_file '$excel_file'
+#end if
+#if str($all_isolates) == "Yes":
+    --all_isolates '$all_isolates'
+#end if
+--output_summary '$output_summary'
+]]></command>
+    <inputs>
+        <conditional name="input_zc_vcf_type_cond">
+            <param name="input_zc_vcf_type" type="select" label="Choose the category of the files to be analyzed">
+                <option value="single" selected="true">A single zero coverage VCF file</option>
+                <option value="collection">A collection of zero coverage VCF files</option>
+            </param>
+            <when value="single">
+                <param name="input_zc_vcf" type="data" format="vcf" label="Zero coverage VCF file">
+                    <validator type="unspecified_build"/>
+                </param>
+            </when>
+            <when value="collection">
+                <param name="input_zc_vcf_collection" format="vcf" type="data_collection" collection_type="list" label="Collection of zero coverage VCF files">
+                    <validator type="unspecified_build"/>
+                </param>
+            </when>
+        </conditional>
+        <param name="input_vcf_collection" format="vcf" type="data_collection" collection_type="list" label="Collection of VCF files against which to analyze the zero coverages VCF file(s)">
+            <validator type="unspecified_build"/>
+        </param>
+        <conditional name="excel_grouper_cond">
+            <param name="excel_grouper" type="select" label="Use Excel file for grouping and filtering?">
+                <option value="yes" selected="true">Yes</option>
+                <option value="no">No</option>
+            </param>
+            <when value="yes">
+                <conditional name="excel_grouper_source_cond">
+                    <param name="excel_grouper_source" type="select" label="Choose the source for the Excel file">
+                        <option value="cached">locally cached</option>
+                        <option value="history">from history</option>
+                    </param>
+                    <when value="cached">
+                        <param name="excel_grouper_file" type="select" label="Excel file" help="Selection will be overridden if it does not match the dbkeys associated with the collection of VCF files being analyzed">
+                            <options from_data_table="vsnp_excel"/>
+                            <validator type="no_options" message="No built-in Excel grouping and filtering datasets are available"/>
+                        </param>
+                    </when>
+                    <when value="history">
+                        <param name="excel_grouper_file" type="data" format="xlsx" label="Excel file">
+                            <validator type="no_options" message="The current history does not include an xlsx dataset that can be used for grouping and filtering"/>
+                        </param>
+                    </when>
+                </conditional>
+            </when>
+            <when value="no"/>
+        </conditional>
+        <param name="all_isolates" type="select" display="radio" label="Create table with all isolates?">
+            <option value="No" selected="true">No</option>
+            <option value="Yes">Yes</option>
+        </param>
+        <param name="processes" type="integer" min="1" max="20" value="8" label="Number of processes for job splitting"/>
+    </inputs>
+    <outputs>
+        <collection name="snps" type="list" label="${tool.name} (SNPs) on ${on_string}">
+            <discover_datasets pattern="__name__" directory="output_snps_dir" format="fasta" />
+        </collection>
+        <collection name="json_avg_mq" type="list" label="${tool.name} (average MQ) on ${on_string}">
+            <discover_datasets pattern="__name__" directory="output_json_avg_mq_dir" format="json" />
+        </collection>
+        <collection name="json_snps" type="list" label="${tool.name} (SNPs as json) on ${on_string}">
+            <discover_datasets pattern="__name__" directory="output_json_snps_dir" format="json" />
+        </collection>
+        <data name="output_summary" format="html" label="${tool.name} (summary) on ${on_string}"/>
+    </outputs>
+    <tests>
+        <test>
+            <param name="input_zc_vcf" value="input_zc_vcf.vcf" ftype="vcf" dbkey="89"/>
+            <param name="input_vcf_collection">
+                <collection type="list">
+                    <element name="SRR8073662_zc.vcf" value="SRR8073662_zc.vcf" dbkey="89"/>
+                    <element name="SRR1792272_zc.vcf" value="SRR1792272_zc.vcf" dbkey="89"/>
+                </collection>
+            </param>
+            <param name="excel_grouper" value="no"/>
+            <output_collection name="snps" type="list">
+                <element name="all_vcf.fasta" file="all_vcf.fasta" ftype="fasta" compare="contains"/>
+            </output_collection>
+            <output_collection name="json_avg_mq" type="list">
+                <element name="all_vcf.json" file="json_avg_mq_all_vcf.json" ftype="json" compare="contains"/>
+            </output_collection>
+            <output_collection name="json_snps" type="list">
+                <element name="all_vcf.json" file="json_all_vcf.json" ftype="json" compare="contains"/>
+            </output_collection>
+            <output name="output_summary" file="output_summary.html" ftype="html" compare="contains"/>
+        </test>
+    </tests>
+    <help>
+**What it does**
+
+Accepts a zero-coverage VCF file (or a collection of them) produced by the **vSNP: add zero coverage** tool
+along with a collection of VCF files that have been aligned with the same reference. The inputs are analyzed
+to discover quality parsimonious SNPs in the zero-coverage VCF file(s).  An Excel spreadsheet containing
+specified SNPs can optiomally be used to filter desired SNP positions by group.  Users can choose whether to
+select a locally cached Excel spreadsheet or one from their current history.
+
+**Required Options**
+
+ * **Choose the category of the files to be analyzed** - select single file or a collection of files, then select the appropriate history item (single VCF item or dataset collection of VCF elements) based on the selected option.
+ * **Collection of VCF files against which to analyze the zero coverages VCF file(s)**  - select a dataset collection from the current history that is associated with the same reference as the selected zero-coverage VCF file(s).
+
+**Additional Options**
+
+ * **Use Excel file for grouping and filtering?** - select Yes to filter desired SNP positions by group.  A cached Excel spreadsheet provides the most widely used SNP positions for grouping, but a custom spreadhseet can be selected from the current history.
+ * **Job Resource Parameters** - an administrator for the Galaxy instance must configure this tool to display this option, so it may not be available.  If it is, you can choose the number of processors to use for tool execution.
+ * **Number of processes for job splitting** - Select the number of processes for splitting the job to shorten execution time.
+</help>
+    <citations>
+        <citation type="bibtex">
+            @misc{None,
+            journal = {None},
+            author = {1. Stuber T},
+            title = {Manuscript in preparation},
+            year = {None},
+            url = {https://github.com/USDA-VS/vSNP},}
+        </citation>
+    </citations>
+</tool>
+