Genomics pipelines

Danforth Center genomics pipeline

Outlined below are the steps taken to create a raw vcf file from paired end raw FASTQ files. This was done for each sequenced accession so a HTCondor DAG Workflow was written to streamline the processing of those ~200 accessions. While some cpu and memory parameters have been included within the example steps below those parameters varied from sample to sample and the workflow has been honed to accomodate that variation. This pipeline is subject to modification based on software updates and changes to software best practices.

Software versions:

Preparing reference genome

Download Sorghum bicolor v3.1 from Phytozome

Generate:

BWA index:

bwa index –a bwtsw Sbicolor_313_v3.0.fa

fasta file index:

samtools faidx Sbicolor_313_v3.0.fa

Sequence dictionary:

java –jar picard.jar CreateSequenceDictionary R=Sbicolor_313_v3.0.fa O=Sbicolor_313_v3.0.dict

Quality trimming and filtering of paired end reads

bbduk2 in=SampleA_R1.fastq in2=SampleA_R2.fastq out=SampleA_R1.PE.fastq.gz \
  out2=SampleA_R2.PE.fastq.gz k=23 mink=11 hdist=1 tpe tbo qtrim=rl trimq=20 \
  minlen=20 rref=adapters_file.fa lref=adapters_file.fa

Aligning reads to the reference

bwa mem –M \
  –R “@RG\tIDSAMPLEA_RG1\tPL:illumina\tPU:FLOWCELL_BARCODE.LANE.SAMPLE_BARCODE_RG_UNIT\tLB:libraryprep-lib1\tSM:SAMPLEA” \
  Sbicolor_313_v3.0.fa SampleA_R1.PE.fastq.gz SampleA_R2.PE.fastq.gz > SAMPLEA.bwa.sam

Convert and Sort bam

Samtools view –bS SAMPLEA.bwa.sam | samtools sort - SAMPLEA.bwa.sorted

Mark Duplicates

java –Xmx8g –jar picard.jar MarkDuplicates MAX_FILE_HANDLES_FOR_READ_ENDS_MAP=1000 \
  REMOVE_DUPLICATES=true INPUT=SAMPLEA.bwa.sorted.bam OUTPUT=SAMPLEA.dedup.bam \
  METRICS_FILES=SAMPLEA.dedup.metrics

Index bam files

samtools index SAMPLEA.dedup.bam

Find intervals to analyze

java –Xmx8g –jar GenomeAnalysisTK.jar –T RealignerTargetCreator \
  –R Sbicolor_313_v3.0.fa –I SAMPLEA.dedup.bam –o SAMPLEA.realignment.intervals

Realign

java –Xmx8g –jar GenomeAnalysisTK.jar –T IndelRealigner –R Sbicolor_313_v3.0.fa \
  –I SAMPLEA.dedup.bam –targetIntervals SAMPLEA.realignment.intervals –o SAMPLEA.dedup.realigned.bam

Variant Calling with GATK HaplotypeCaller

java –Xmx8g –jar GenomeAnalysisTK.jar –T HaplotypeCaller –R Sbicolor_313_v3.0.fa \
  –I SAMPLEA.dedup.realigned.bam --emitRefConfidence GVCF --pcr_indel_model NONE \
  -o SAMPLEA.output.raw.snps.indels.g.vcf

Above this point is the workflow for the creation of the gVCF files for this project. The following additional steps were used to create the Hapmap file

Combining gVCFs with GATK CombineGVCFs

NOTE: This project has 363 gvcfs: multiple instances of CombineGVCFs, with unique subsets of gvcf files, were run in parallel to speed up this step below are examples

java –Xmx8g –jar GenomeAnalysisTK.jar –T CombineGVCFs –R Sbicolor_313_v3.0.fa \
  -V SAMPLEA.output.raw.snps.indels.g.vcf --variant SAMPLEB.output.raw.snps.indels.g.vcf\
  -V SAMPLEC.output.raw.snps.indels.g.vcf -o SamplesABC_combined_gvcfs.vcf

java –Xmx8g –jar GenomeAnalysisTK.jar –T CombineGVCFs –R Sbicolor_313_v3.0.fa \
  --variant SAMPLED.output.raw.snps.indels.g.vcf -V SAMPLEE.output.raw.snps.indels.g.vcf \
  -V SAMPLEF.output.raw.snps.indels.g.vcf -o SamplesDEF_combined_gvcfs.vcf

Joint genotyping on gVCF files with GATK GenotypeGVCFs

java –Xmx8g –jar GenomeAnalysisTK.jar –T GenotypeGVCFs –R Sbicolor_313_v3.0.fa \
  -V SamplesABC_combined_gvcfs.vcf -V SamplesDEF_combined_gvcfs.vcf -o all_combined_Genotyped_lines.vcf

Applying hard SNP filters with GATK VariantFiltration

java –Xmx8g –jar GenomeAnalysisTK.jar –T VariantFiltration –R Sbicolor_313_v3.0.fa \
  -V all_combined_Genotyped_lines.vcf -o all_combined_Genotyped_lines_filtered.vcf \
  --filterExpression "QD < 2.0" --filterName "QD" --filterExpression "FS > 60.0" \
  --filterName "FS" --filterExpression "MQ < 40.0" --filterName "MQ" --filterExpression "MQRankSum < -12.5" \
  --filterName "MQRankSum" --filterExpression "ReadPosRankSum < -8.0" --filterName "ReadPosRankSum"

Filter and recode VCF with VCFtools

vcftools --vcf all_combined_Genotyped_lines_filtered.vcf --min-alleles 2 --max-alleles 2 \
  --out all_combined_Genotyped_lines_vcftools.filtered.recode.vcf --max-missing 0.2 --recode

Adapt VCF for use with Tassel5

tassel-5-standalone/run_pipeline.pl -Xms75G -Xmx265G -SortGenotypeFilePlugin \
  -inputFile all_combined_Genotyped_lines_vcftools.filtered.recode.vcf \
  -outFile all_combined_Genotyped_lines_vcftools.filtered.recode.sorted.vcf -fileType VCF

Convert VCF to Hapmap with Tassel5

tassel-5-standalone/run_pipeline.pl -Xms75G -Xmx290G -fork1 -vcf \
  all_combined_Genotyped_lines_vcftools.filtered.recode.sorted.vcf -export -exportType Hapmap -runfork1

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