UGP Variant Pipeline 1.3.0

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Utah Genome Project

Jan. 2015 
Variant Calling Pipeline Version 1.3.0

Software Versions

  • cApTUrE is a lightweight NGS pipeline, created for the
 Utah Genome Project (UGP)
  • BWA: 0.7.10
  • GATK: 3.3-0
  • SamTools: 0.2.0
  • Samblaster
  • Sambamba
  • FastQC v0.10.1

Data Source

Data sets used for the variant calling pipeline come from the Broad GSA (GATK) group as the 'GATK resource bundle version 2.8 

wget -r ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/2.5/b37

Reference Genome (GRCh37) Now includes phix sequence.

  • human_g1k_v37_decoy.fasta

Call region file generated from NCBI

  • GRCh37 GFF3

VCF files for RealignerTargetCreator knowns and dbsnp for BaseRecalibrator.

  • known_indel: Mills_and_1000G_gold_standard.indels.b37.vcf
  • known_indel: 1000G_phase1.indels.b37.vcf
  • known_dbsnp: dbsnp_137.b37.vcf

Background Files

  • We have created 1000Genomes (BWA mem/GATK 3.0+) background files to be ran concurrently with the GenotypeGVCFs step.

Groups Currently completed:

  • CEU
  • GBR
  • FIN

Version 1.0.5 background files have been updated to show only the indviduals of each group, not the file names.

This is a complete list of the background individuals for run completed > 1.0.5 [1] 

If you would like a copy of the current files, we have made a public AWS s3 bucket
Using s3cmd execute the following command: 
s3cmd get s3://ugp-1k-backgrounds --recursive

Alternatively to access the files without s3cmd the following use the following URLs:
http://s3-us-west-2.amazonaws.com/ugp-1k-backgrounds/CEU_mergeGvcf.vcf
http://s3-us-west-2.amazonaws.com/ugp-1k-backgrounds/CEU_mergeGvcf.vcf.idx
http://s3-us-west-2.amazonaws.com/ugp-1k-backgrounds/FIN_mergeGvcf.vcf
http://s3-us-west-2.amazonaws.com/ugp-1k-backgrounds/FIN_mergeGvcf.vcf.idx
http://s3-us-west-2.amazonaws.com/ugp-1k-backgrounds/GBR_mergeGvcf.vcf
http://s3-us-west-2.amazonaws.com/ugp-1k-backgrounds/GBR_mergeGvcf.vcf.idx

Resource files for VariantRecalibrator_SNP

  • hapmap_3.3.b37.vcf
  • 1000G_omni2.5.b37.vcf
  • 1000G_phase1.snps.high_confidence.b37.vcf

Resource files for VariantRecalibrator_INDEL

  • Mills_and_1000G_gold_standard.indels.b37.vcf
  • 1000G_phase1.indels.b37.vcf

Sequencing

This pipeline is designed for 100 bp (or greater) Illumina HiSeq PE exome or WGS sequence data with Sanger/Illumina 1.9 quality encoding, and uses Illumina naming convention found here [2]

Validate File Integrity with md5sum

An md5sum signature should be provided for each FastQ file by the sequencing center. After the file has been downloaded, locally check the md5sum to be sure that no data corruption occurred during the file transfer. 

md5sum file.fastq > file_local.md5
diff file_local.md5 file_provided.md5
Now the pipeline runs md5_check to validation the results and will quit if errors are found.

If the md5sum signature differs from that provided for the file:

  • Check to be sure you have the correct file.
  • Check if the md5sum was calculated on that compressed or uncompressed file by the provider and be sure to do the same with the local copy.
  • Try the download again.
  • Contact the sequence provider.

FastQ File Analyses

/scratch/ucgd/lustre/u0413537/software/FastQC/ 

fastqc --threads # -o <output dir> -f fastq fastq-file.fq.gz 2> fastqc_run.log-#

From the sumamry.txt report we check

  • FAIL sections

From the fastqc_data.txt file we check the following values:

  • Encoding (must be Sanger / Illumina 1.9)
  • Total Sequences (Currently set to 30000000)
  • Filtered Sequences (Currently set to less then 5)
  • Sequence length (must be >= 100 bp)
  • %GC (45 < x < 55)
  • Total Duplicate Percentage (Currently set to 60.0)

The pipeline now runs fastqc_check and output these result into QC-report.txt.

Indexing

The following indexing is required using BWA, Picard and SamTools. GATK requires all three. However this step only needs to be done once "per-machine".

  • BWA
bwa index -a bwtsw human_g1k_v37_decoy.fasta
  • Picard
java -jar CreateSequenceDictionary.jar R=human_g1k_v37_decoy.fasta O=human_g1k_v37_decoy.dic
  • SamTools
samtools faidx human_g1k_v37_decoy.fasta

Alignment

Align reads to the genome with bwa.

The 'BWA-mem' program will find the reference coordinates of the input reads (independent of their mate-pair). The following parameters are those used by the 1KG project and GATK for aligning Illumina data. 

bwa mem -R "read group" human_g1k_v37_decoy.fasta Sample1_L1_R1.fq Sample1_L1_R2.fq | samblaster |sambamba view -f bam -l 0 -S /dev/stdin | 
sambamba sort -m 50G -o *_#_sorted_Dedup.bam

BAM File Analyses

  • idxstats
samtools idxstats [dedup bam files] > dedup-bamfile.stats
  • flagstat

/scratch/ucgd/lustre/u0413537/software/samtools-0.1.19/ 

samtools flagstat _#_sorted_Dedup.bam > _#_sorted_Dedup.flagstat 2> flagstat.log-#

BAM Merging

  • sambamba

Merging lane BAM files into single individual BAM file. 

/scratch/ucgd/lustre/u0413537/software/sambamba/ 
sambamba merge  
--nthreads # 
individual_#_sorted_Dedup_merged.bam 
[individual_#_sorted_Dedup.bam files]

Local Realignment of Indels

  • RealignerTargetCreator

This is where the tasks are broken into chromosomal regions. 

java -jar -Xmx#g -XX:ParallelGCThreads=# -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T RealignerTargetCreator 
   -R human_g1k_v37_decoy.fasta 
   -I *_sorted_Dedup.bam 
   --num_threads #  
   --known Mills_and_1000G_gold_standard.indels.b37.vcf
   --known 1000G_phase1.indels.b37.vcf  
   -L chr#_region_file.list 
   -o *_chr#_realign.intervals 
   &> RealignerTargetCreator.log-#
  • IndelRealigner
java -jar -Xmx#g -XX:ParallelGCThreads=# -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T IndelRealigner 
   -R human_g1k_v37_decoy.fasta 
   -I *_sorted_Dedup.bam 
   -L chr#_region_file.list
   -targetIntervals *_chr#_realign.intervals 
   -known Mills_and_1000G_gold_standard.indels.b37.vcf 
   -known 1000G_phase1.indels.b37.vcf 
   -o *_sorted_Dedup_realign_chr#.bam 
   &> IndelRealigner.log-1

BaseRecalibration & PrintReads

  • BaseRecalibrator
java -jar -Xmx#g -XX:ParallelGCThreads=# -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T BaseRecalibrator 
   -R /human_g1k_v37_decoy.fasta 
   -I *_sorted_Dedup_realign_chr#.bam 
   --num_cpu_threads_per_data_thread #  
   --knownSites dbsnp_137.b37.vcf
   --knownSites Mills_and_1000G_gold_standard.indels.b37.vcf 
   --knownSites 1000G_phase1.indels.b37.vcf  
   -o *_sorted_Dedup_realign_chr#_recal_data.table 
   &> BaseRecalibrator.log-#
  • PrintReads
java -jar -Xmx#g -XX:ParallelGCThreads=# -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T PrintReads 
   -R human_g1k_v37_decoy.fasta 
   -I *_sorted_Dedup_realign_chr#.bam
   --num_cpu_threads_per_data_thread #  
   -BQSR *_sorted_Dedup_realign_chr#_recal_data.table 
   -o *_sorted_Dedup_realign_chr#_recal.bam 
   &> PrintReads.log-#

Variant Calling

HaplotypeCaller

  • Now HaplotypeCaller handels SNP and INDEL calls.
java -jar -Xmx#g -XX:ParallelGCThreads=# -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T HaplotypeCaller 
   -R human_g1k_v37_decoy.fasta 
   --min_base_quality_score 20 
   --variant_index_parameter 128000 
   --emitRefConfidence GVCF 
   --standard_min_confidence_threshold_for_calling 30.0 
   --num_cpu_threads_per_data_thread # 
   --variant_index_type LINEAR 
   --standard_min_confidence_threshold_for_emitting 30.0  
   -I *_sorted_Dedup_realign_chr*_recal.bam 
   -L chr#_region_file.list
   -o chr#_region_*.raw.snps.indels.gvcf 
   &> HaplotypeCaller.log-#

CatVariants

Collect all individual gvcf files. 

java -cp GenomeAnalysisTK.jar org.broadinstitute.gatk.tools.CatVariants 
   -R human_g1k_v37_decoy.fasta 
   --assumeSorted  
   -V chr#_region_*.raw.snps.indels.vcf 
   -V [ ... ]
   -out *.raw.snps.indels.gCat.vcf 
   &> CatVariants.log-*

CombineGVCFs

Collect all the chromosomal cat files. This is also the step where mergeGvcf are collected for future runs. 

java -jar -Xmx#g -XX:ParallelGCThreads=# GenomeAnalysisTK.jar  
   -T CombineGVCFs 
   -R human_g1k_v37_decoy.fasta 
   --variant *.raw.snps.indels.gCat.vcf
   --variant [ ... ]
   -o cApTUrE_*_final_mergeGvcf.vcf 
   &> CombineGVCF.log-*

GenotypeGVCFs

java -jar -Xmx#g -XX:ParallelGCThreads=# GenomeAnalysisTK.jar 
   -T GenotypeGVCFs 
   -R human_g1k_v37_decoy.fasta 
   --num_threads #  
   --variant cApTUrE_*_final_mergeGvcf.vcf 
   --variant CEU_mergeGvcf.vcf 
   --variant GBR_mergeGvcf.vcf 
   --variant FIN_mergeGvcf.vcf 
   -L chr#_region_file.list 
   -o cApTUrE_*_#_genotyped.vcf 
   &> GenotypeGVCF.log-#

Combine_Genotyped

Collect all the individual genotype steps. 

java -cp GenomeAnalysisTK.jar org.broadinstitute.gatk.tools.CatVariants 
   -R human_g1k_v37_decoy.fasta 
   --assumeSorted  
   -V cApTUrE_*_#_genotyped.vcf 
   -V [ ... ] 
   -out cApTUrE_*_genotyped.vcf 
   &> Combine_Genotyped.log-#

VariantRecalibrator

  • SNP Recalibration
java -jar -Xmx#g -XX:ParallelGCThreads=# -Djava.io.tmpdir=tmp GenomeAnalysisTK.jar  
   -T VariantRecalibrator 
   -R human_g1k_v37_decoy.fasta 
   --minNumBadVariants 5000 
   --num_threads #  
   -resource:hapmap,known=false,training=true,truth=true,prior=15.0 hapmap_3.3.b37.vcf 
   -resource:omni,known=false,training=true,truth=true,prior=12.0 1000G_omni2.5.b37.vcf 
   -resource:1000G,known=false,training=true,truth=false,prior=10.0 1000G_phase1.snps.high_confidence.b37.vcf 
   -an QD 
   -an MQRankSum 
   -an ReadPosRankSum 
   -an FS 
   -an InbreedingCoeff 
   -input cApTUrE_*_genotyped.vcf 
   -recalFile cApTUrE_*_snp_recal 
   -tranchesFile cApTUrE_*_snp_tranches 
   -rscriptFile cApTUrE_*_snp_plots.R 
   -mode SNP 
   &> VariantRecalibrator_SNP.log-#
  • INDEL Recalibration
java -jar -Xmx#g -XX:ParallelGCThreads=# -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T VariantRecalibrator 
   -R human_g1k_v37_decoy.fasta 
   --minNumBadVariants 5000 
   --num_threads #  
   -resource:mills,known=false,training=true,truth=true,prior=12.0 Mills_and_1000G_gold_standard.indels.b37.vcf 
   -resource:1000G,known=false,training=true,truth=true,prior=10.0 1000G_phase1.indels.b37.vcf 
   -an MQRankSum 
   -an ReadPosRankSum 
   -an FS 
   -input cApTUrE_*_genotyped.vcf 
   -recalFile cApTUrE_*_indel_recal 
   -tranchesFile cApTUrE_*_indel_tranches 
   -rscriptFile cApTUrE_*_indel_plots.R 
   -mode INDEL 
   &> VariantRecalibrator_INDEL.log-#

ApplyRecalibration

  • SNP Apply
java -jar -Xmx#g -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T ApplyRecalibration 
   -R human_g1k_v37_decoy.fasta 
   --ts_filter_level 99.5 
   --excludeFiltered 
   --num_threads #  
   -input cApTUrE_*_genotyped.vcf 
   -recalFile cApTUrE_*_snp_recal 
   -tranchesFile cApTUrE_*_snp_tranches 
   -mode SNP 
   -o cApTUrE_*_recal_SNP.vcf 
   &> ApplyRecalibration_SNP.log-*
  • INDEL Apply
java -jar -Xmx#g -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar
   -T ApplyRecalibration 
   -R human_g1k_v37_decoy.fasta 
   --ts_filter_level 99.0 
   --excludeFiltered 
   --num_threads #  
   -input cApTUrE_*_genotyped.vcf 
   -recalFile cApTUrE_*_indel_recal 
   -tranchesFile cApTUrE_*_indel_tranches 
   -mode INDEL 
   -o cApTUrE_*_recal_INDEL.vcf 
   &> ApplyRecalibration_INDEL.log-*

CombineVarients

These command will combine INDEL and SNP files into a single VCF file.

  • CombineVarients
java -jar -Xmx#g -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T CombineVariants 
   -R human_g1k_v37_decoy.fasta 
   --num_threads # 
   --genotypemergeoption UNSORTED 
   --variant cApTUrE_*_recal_SNP.vcf  
   --variant cApTUrE_*_recal_INDEL.vcf  
   -o cApTUrE_*_Combined.vcf 
   &> CombineVariants.log-*
  • SelectVariants
java -jar -Xmx#g -Djava.io.tmpdir=/tmp GenomeAnalysisTK.jar 
   -T SelectVariants 
   -R human_g1k_v37_decoy.fasta 
   --variant cApTUrE_*_Combined.vcf  
   -select "DP > 100" 
   -o cApTUrE_*_Final+Backgrounds.vcf 
   &> SelectVariants.log-*

Variant File QC

Quality Metrics on variants

  • Ti/Tv Ratio (2.1 for WGS ~2.8 for exome)
  • HapMap concordance
  • SNV/Indel Counts
  • Rare variant enrichment
  • DP
  • Q
  • GQ
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