Evidence map›Paper›PMID 31249686›Full record

ArticleJournal of animal science and biotechnology2019

The GATK joint genotyping workflow is appropriate for calling variants in RNA-seq experiments.

Jean-Simon Brouard, Flavio Schenkel, Andrew Marete, Nathalie Bissonnette

Abstract read
In one paragraph

Article in Journal of animal science and biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

90 citing papers in PubMed.

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  20. Genes and pathways determining flowering time variation in temperate-adapted sorghum.The Plant journal : for cell and molecular biology · 2025
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30 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jean-Simon Brouard1Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8 Canada.
Flavio Schenkel2Center of Genetic Improvement of Livestock, University of Guelph, Guelph, ON N1G 2W1 Canada.
Andrew Marete1Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8 Canada.
Nathalie Bissonnette1Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, QC J1M 0C8 Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Genome Analysis Toolkit (GATK) is a popular set of programs for discovering and genotyping variants from next-generation sequencing data. The current GATK recommendation for RNA sequencing (RNA-seq) is to perform variant calling from individual samples, with the drawback that only variable positions are reported. Versions 3.0 and above of GATK offer the possibility of calling DNA variants on cohorts of samples using the HaplotypeCaller algorithm in Genomic Variant Call Format (GVCF) mode. Using this approach, variants are called individually on each sample, generating one GVCF file per sample that lists genotype likelihoods and their genome annotations. In a second step, variants are called from the GVCF files through a joint genotyping analysis. This strategy is more flexible and reduces computational challenges in comparison to the traditional joint discovery workflow. Using a GVCF workflow for mining SNP in RNA-seq data provides substantial advantages, including reporting homozygous genotypes for the reference allele as well as missing data. Taking advantage of RNA-seq data derived from primary macrophages isolated from 50 cows, the GATK joint genotyping method for calling variants on RNA-seq data was validated by comparing this approach to a so-called "per-sample" method. In addition, pair-wise comparisons of the two methods were performed to evaluate their respective sensitivity, precision and accuracy using DNA genotypes from a companion study including the same 50 cows genotyped using either genotyping-by-sequencing or with the Bovine SNP50 Beadchip (imputed to the Bovine high density). Results indicate that both approaches are very close in their capacity of detecting reference variants and that the joint genotyping method is more sensitive than the per-sample method. Given that the joint genotyping method is more flexible and technically easier, we recommend this approach for variant calling in RNA-seq experiments.

Indexed as

GATKGVCFJoint genotypingRNA-seqSNP

Identifiers

PMID31249686
PMCPMC6587293

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.