Short-read aligner performance in germline variant identification

Richard Wilton; Alexander S Szalay

doi:10.1093/bioinformatics/btad480

Short-read aligner performance in germline variant identification

Bioinformatics. 2023 Aug 1;39(8):btad480. doi: 10.1093/bioinformatics/btad480.

Authors

Richard Wilton¹, Alexander S Szalay^{1

2}

Affiliations

¹ Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, United States.
² Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, United States.

Abstract

Motivation: Read alignment is an essential first step in the characterization of DNA sequence variation. The accuracy of variant-calling results depends not only on the quality of read alignment and variant-calling software but also on the interaction between these complex software tools.

Results: In this review, we evaluate short-read aligner performance with the goal of optimizing germline variant-calling accuracy. We examine the performance of three general-purpose short-read aligners-BWA-MEM, Bowtie 2, and Arioc-in conjunction with three germline variant callers: DeepVariant, FreeBayes, and GATK HaplotypeCaller. We discuss the behavior of the read aligners with regard to the data elements on which the variant callers rely, and illustrate how the runtime configurations of these software tools combine to affect variant-calling performance.

Availability and implementation: The quick brown fox jumps over the lazy dog.

Publication types

Review
Research Support, N.I.H., Extramural

MeSH terms

Germ Cells
High-Throughput Nucleotide Sequencing* / methods
Sequence Analysis, DNA / methods
Software*

Grants and funding

U54 CA274370/CA/NCI NIH HHS/United States