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Updated: Sep 6, 2025
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Detection of Rare Mutations in CtDNA Using Next Generation Sequencing
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Variant Calling from RNA-seq Data Using the GATK Joint Genotyping Workflow
Jean-Simon Brouard1, Nathalie Bissonnette2
1Agriculture and Agri-Food Canada, Sherbrooke, QC, Canada. jean-simon.brouard@agr.gc.ca.
Methods in Molecular Biology (Clifton, N.J.)
|June 25, 2022
Summary
This study presents a novel method for variant calling in RNA sequencing (RNAseq) data using the Genome Analysis Toolkit (GATK). The approach enables joint genotyping analysis, improving variant discovery and identifying potential disease associations.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- The Genome Analysis Toolkit (GATK) offers advanced pipelines for variant discovery.
- Current GATK pipelines for RNA sequencing (RNAseq) data are per-sample and lack joint genotyping capabilities.
- Modern bioinformatics workflows offer improved variant calling strategies.
Purpose of the Study:
- To describe a method for combining modern GATK commands for variant calling on RNAseq data.
- To provide a tutorial for RNAseq variant discovery from raw reads to filtered variants.
- To demonstrate the utility of the method by identifying variants associated with bovine paratuberculosis.
Main Methods:
- Integration of modern GATK commands from different workflows.
- Application of the combined workflow to RNAseq data.
- Variant filtering and association analysis.
Main Results:
- A comprehensive tutorial for RNAseq variant calling using GATK.
- Successful identification of variants in RNAseq data.
- Discovery of variants potentially linked to bovine paratuberculosis.
Conclusions:
- The described method enhances GATK's utility for RNAseq variant analysis.
- Combining GATK commands enables joint genotyping for RNAseq data.
- This approach facilitates the discovery of disease-associated variants.
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