Precision Medicine Bioinformatics

Introduction to bioinformatics for DNA and RNA sequence analysis

Somatic SV Calling

Manta is a structural variant caller maintained by Illumina and optimized for calling somatic variation in tumor/normal pairs. In this section we will use Manta to call structural variants in our WGS data but first let’s go over what a structural variant actually is. Structural variants are rearrangements in DNA involving a breakpoint(s). Generally speaking structural variants can fall into four categories:

  1. Insertions: a region is inserted into the DNA
  2. Deletions: a region is deleted in the DNA
  3. Inversions: a section of DNA is reversed
  4. Translocations: a section of DNA is remved and re-inserted in a new region

Running manta is a two step process. The first step is configuring manta to run with, it is at this step where we specify the inputs and any additional ouptions such as the output directory. The next step executes the manta workflow and will output the results based on the configuration in the first step. We should note here that manta requires python 2 in order to run, we’ve configured a conda environment for manta which will use python 2 so we need to activate that python environment first. From there we run the script with the following options:

  1. –normalBam: path to normal bam
  2. –tumorBam: path to tumor bam
  3. –referenceFasta: path to indexed reference fasta
  4. –runDir: path to directory where results will be stored
# make directory for results
mkdir -p ~/workspace/somatic/manta_wgs
cd ~/workspace/somatic/manta_wgs

# source the manta config Environment
source activate manta

# run the manta config script
python /usr/local/bin/manta-1.4.0.centos6_x86_64/bin/ --normalBam=/workspace/align/WGS_Norm_merged_sorted_mrkdup_bqsr.bam --tumorBam=/workspace/align/WGS_Tumor_merged_sorted_mrkdup_bqsr.bam --referenceFasta=/workspace/inputs/references/genome/ref_genome.fa --runDir=/workspace/somatic/manta_wgs/

Next with everything configured we can go ahead and run manta. All we have to do here is run the script the configuration step created in the previous step and specify if we are running this locally or on a cluster with the -m The specific options we give and what they mean are provided below.

  1. -m local: specifies we are running manta on a local computer
  2. -j 8: number of jobs to launch at once
  3. -g 60: run with 60 gigabytes
# run manta
python /workspace/somatic/manta_wgs/ -m local -j 8 -g 60

# deactivate environment
source deactivate

The output of manta is quite verbose, however in gerneral the files we care about are in the /workspace/somatic/manta_wgs/results/variants folder. Specifically as we are interested in somatic events occuring in the tumor sample we care about the somaticSV.vcf.gz file.