Implementing Sarek Pipeline on the University of Florida High Performance Computing Environment

University of Florida High Performance Computing Implementation of Sarek's Pipeline to detect germline or somatic variants from normal or tumour/normal whole-genome, whole exome, or targeted sequencing.

The original Sarek repository has been modified and retrofitted to run on the UF HPC/HiPerGator and instructions are given below.

Create an University of Florida Research Computing Account

First, sign up for UFRC account here.

Connect to UFRC Environment (HiPerGator) Using Your Gatorlink Username and Password.

ssh username@hpg.rc.ufl.edu

Download Modified Sarek Pipeline From This Repository

git clone --recursive https://github.com/jongtaek-kim/Sarek UFRC-Sarek
cd UFRC-Sarek

Setup your UFRC Environment For Interactive Testing Of Sarek Pipeline and Nextflow Script

$ module load ufrc
$ srundev --time=01:00:00
$ module load nextflow/0.32.0
$ module load singularity/2.5.2

Scheduling Jobs On The HiPerGator Using SLURM

The configuration files have been modified for HiPerGator and a sample SLURM script is provided here.

Download the complete GRCh37 Reference files as shown here or simply copy them from /ufrc/djlemas/jtkim1/UFRC-Sarek/References/GRCh37 if you are inside HiPerGator. Modify the genomes config files (already modified in this git repo).

Make a folder for your NGS data. We placed all our FASTQ files in the "UF-data/UF_Testset" folder.

Run the Pipeline on Real NGS Data. Whole Exome Sequencing Data from Illumina NextSeq Series is Illustrated, which normally outputs a paired-end reads (Forward R1 and Reverse R2 Reads from each lane).

1. Example TSV file (UFsampledata.tsv) for a normal/tumor pair with FASTQ files shown below. The complete descriptions are here.

EATL1	XX	0	Normal1	Lane1	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L001_R1_001.fastq.gz	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L001_R2_001.fastq.gz
EATL1	XX	0	Normal1	Lane2	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L002_R1_001.fastq.gz	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L002_R2_001.fastq.gz
EATL1	XX	0	Normal1	Lane3	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L003_R1_001.fastq.gz	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L003_R2_001.fastq.gz
EATL1	XX	0	Normal1	Lane4	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L004_R1_001.fastq.gz	UF-data/UF_Testset/Normal1/NS-17-11-BC05-72_S4_L004_R2_001.fastq.gz
EATL1	XX	1	Tumor1	Lane1	UF-data/UF_Testset/Tumor1/W6172-00_S1_L001_R1_001.fastq.gz	UF-data/UF_Testset/Tumor1/W6172-00_S1_L001_R2_001.fastq.gz
EATL1	XX	1	Tumor1	Lane2	UF-data/UF_Testset/Tumor1/W6172-00_S1_L002_R1_001.fastq.gz	UF-data/UF_Testset/Tumor1/W6172-00_S1_L002_R2_001.fastq.gz
EATL1	XX	1	Tumor1	Lane3	UF-data/UF_Testset/Tumor1/W6172-00_S1_L003_R1_001.fastq.gz	UF-data/UF_Testset/Tumor1/W6172-00_S1_L003_R2_001.fastq.gz
EATL1	XX	1	Tumor1	Lane4	UF-data/UF_Testset/Tumor1/W6172-00_S1_L004_R1_001.fastq.gz	UF-data/UF_Testset/Tumor1/W6172-00_S1_L004_R2_001.fastq.gz

2. Run the Nextflow Script as shown below.

nextflow run main.nf --sample UF-data/UFsampledata.tsv  --step mapping --genome GRCh37 --genome_base References/GRCh37   --tag latest -profile singularity

 

 

Application of Sarek Whole Exome Bioinformatics Pipeline to Cancer Immuno-Oncology Strategy.

 

Whole Exome Sequencing is the "Gold Standard" for TMB Calculation.

TMB represents the amount of neoantigen that immune system has not previously been exposed to, in context of cancer and Immunotherapy.

 

TMB as a biomarker for response to Immunotherapy.

High TMB is associated with response to Immunotherapy such as CTLA-4 and/or PD-1 blockade.

 

*Supplement Above TMB Calculation with Microsatellite Instability Analysis here and Mutational Signature Analysis here.

 

For More Information About Sarek Repository and Pipeline, See Below.

 

 

An open-source analysis pipeline to detect germline or somatic variants from whole genome or targeted sequencing

Introduction

Previously known as the Cancer Analysis Workflow (CAW), Sarek is a workflow designed to run analyses on WGS data from regular samples or tumour / normal pairs, including relapse samples if required.

It's built using Nextflow, a domain specific language for workflow building. Software dependencies are handled using Docker or Singularity - container technologies that provide excellent reproducibility and ease of use. Singularity has been designed specifically for high-performance computing environments. This means that although Sarek has been primarily designed for use with the Swedish UPPMAX HPC systems, it should be able to run on any system that supports these two tools.

Sarek was developed at the National Genomics Infastructure and National Bioinformatics Infastructure Sweden which are both platforms at SciLifeLab. It is listed on the Elixir - Tools and Data Services Registry.

Workflow steps

Sarek is built with several workflow scripts. A wrapper script contained within the repository makes it easy to run the different workflow scripts as a single job. To test your installation, follow the tests documentation.

Raw FastQ files or aligned BAM files (with or without realignment & recalibration) can be used as inputs. You can choose which variant callers to use, plus the pipeline is capable of accommodating additional variant calling software or CNV callers if required.

The worflow steps and tools used are as follows:

1. Preprocessing - main.nf (based on GATK best practices)
   • Map reads to Reference
     • BWA
   • Mark Duplicates
     • GATK MarkDuplicates
   • Base (Quality Score) Recalibration
     • GATK BaseRecalibrator
     • GATK ApplyBQSR
2. Germline variant calling - germlineVC.nf
   • SNVs and small indels
     • GATK HaplotyeCaller
     • Strelka2
   • Structural variants
     • Manta
3. Somatic variant calling - somaticVC.nf (optional)
   • SNVs and small indels
     • MuTect2
     • Freebayes
     • Strelka2
   • Structural variants
     • Manta
   • Sample heterogeneity, ploidy and CNVs
     • ASCAT
4. Annotation - annotate.nf (optional)
   • Variant annotation
     • SnpEff
     • VEP (Variant Effect Predictor)
5. Reporting - runMultiQC.nf
   • Reporting
     • MultiQC

Documentation

The Sarek pipeline comes with documentation in the docs/ directory:

1. Installation documentation
2. Installation documentation specific for UPPMAX rackham
3. Installation documentation specific for UPPMAX bianca
4. Tests documentation
5. Reference files documentation
6. Configuration and profiles documentation
7. Intervals documentation
8. Running the pipeline
9. Command line parameters
10. Examples
11. Input files documentation
12. Processes documentation
13. Documentation about containers
14. More information about ASCAT
15. Output documentation structure

Contributions & Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on Gitter or contact us: maxime.garcia@scilifelab.se, szilveszter.juhos@scilifelab.se

CHANGELOG

• CHANGELOG

Credits

Main authors:

• Maxime Garcia
• Szilveszter Juhos

Helpful contributors:

• Johannes Alneberg
• Sebastian DiLorenzo
• Jesper Eisfeldt
• Phil Ewels
• Max Käller
• Malin Larsson
• Marcel Martin
• Björn Nystedt
• Pall Olason
• Aron Skaftason

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