Lesson

Variant Calling - Automating a workflow

Learning Objectives:

What’s the goal for this lesson?

• Use a series of command line tools to perform a variant calling workflow
• Use a For loop from the previous lesson to help automate repetitive tasks
• Group a series of sequential commands into a script to automate a workflow

To get started with this lesson, we first need to be in an interactive session on the HPC so we are not running any computation on the login node. Next we will need to grab some data from an outside server using wget on the command line.

Make sure you are in the ~/lus/bio_workshop directory first (or a directory on your ~/lus so you are using the appropriate scratch storage on the HPC)

$ cd ~/lus/bio_workshop
$ wget http://reactomerelease.oicr.on.ca/download/archive/variant_calling.tar.gz

The file ‘variant_calling.tar.gz’ is what is commonly called a “tarball”, which is a compressed archive similar to the .zip files we have seen before. We can decompress this archive using the command below.

$ tar -zxvf variant_calling.tar.gz

This will create a directory tree that contains some input data (reference genome and fastq files) and a shell script that details the series of commands used to run the variant calling workflow.

variant_calling
├── ref_genome
│   └── ecoli_rel606.fasta
├── run_variant_calling.sh
└── trimmed_fastq
    ├── SRR097977.fastq
    ├── SRR098026.fastq
    ├── SRR098027.fastq
    ├── SRR098028.fastq
    ├── SRR098281.fastq
    └── SRR098283.fastq

Without getting into the details yet, the variant calling workflow will do the following steps

1. Index the reference genome for use by bwa and samtools
2. Align reads to reference genome
3. Convert the format of the alignment to sorted BAM, with some intermediate steps.
4. Calculate the read coverage of positions in the genome
5. Detect the single nucleotide polymorphisms (SNPs)
6. Filter and report the SNP variants in VCF (variant calling format)

Let’s walk through the commands in the workflow

The first command is to change to our working directory so the script can find all the files it expects

$ cd ~/lus/bio_workshop/variant_calling

Assign the name/location of our reference genome to a variable ($genome)

$ genome=data/ref_genome/ecoli_rel606.fasta

We need to index the reference genome for bwa and samtools. bwa and samtools are programs that are pre-installed on the HPC but you need to use the ‘module load’ command to load the appropriate version of each tool - (you can use ‘module avail’ to list the available modules and then load the correct one).

module load prod/samtools1.2 bioinfo/bwa/0.7.15 prod/bcftools-1.2
bwa index $genome
samtools faidx $genome

Create output paths for various intermediate and result files. The -p option means mkdir will create the whole path if it does not exist (no error or message will be given if it does exist)

$ mkdir -p results/sai
$ mkdir -p results/sam
$ mkdir -p results/bam
$ mkdir -p results/bcf
$ mkdir -p results/vcf

We will now use a loop to run the variant calling workflow of each of our fastq files, so the list of commands below will be executed once for each fastq file.

We will start the loop like this, so the name of each fastq file will by assigned to $fq

$ for fq in data/trimmed_fastq/*.fastq
> do
> # etc...

In the script, it is a good idea to use echo for debugging/reporting to the screen

$ echo "working with file $fq"

This command will extract the base name of the file (without the path and .fastq extension) and assign it to the $base variable

$ base=$(basename $fq .fastq)
$ echo "base name is $base"

We will assign various file names to variables both for convenience but also to make it easier to see what is going on in the commands below.

$ fq=data/trimmed_fastq/$base\.fastq
$ sai=results/sai/$base\_aligned.sai
$ sam=results/sam/$base\_aligned.sam
$ bam=results/bam/$base\_aligned.bam
$ sorted_bam=results/bam/$base\_aligned_sorted.bam
$ raw_bcf=results/bcf/$base\_raw.bcf
$ variants=results/bcf/$base\_variants.bcf
$ final_variants=results/vcf/$base\_final_variants.vcf    

Our data are now staged. The series of command below will run the steps of the analytical workflow

Align the reads to the reference genome

$ bwa aln $genome $fq > $sai

Convert the output to the SAM format

$ bwa samse $genome $sai $fq > $sam

Convert the SAM file to BAM format

$ samtools view -S -b $sam > $bam

Sort the BAM file

$ samtools sort -f $bam $sorted_bam

Index the BAM file for display purposes

$ samtools index $sorted_bam

Do the first pass on variant calling by counting read coverage

$ samtools mpileup -g -f $genome $sorted_bam > $raw_bcf

Do the SNP calling with bcftools

$ bcftools view -bvcg $raw_bcf > $variants

Filter the SNPs for the final output

$ bcftools view $variants | vcfutils.pl varFilter - > $final_variants

Exercise Convert the above commands into a script **