Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218, United States.
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, United States.
Bioinformatics. 2023 Aug 1;39(8). doi: 10.1093/bioinformatics/btad480.
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.
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.
The quick brown fox jumps over the lazy dog.
读段比对是 DNA 序列变异特征描述的首要基本步骤。变异调用结果的准确性不仅取决于读段比对和变异调用软件的质量，还取决于这些复杂软件工具之间的相互作用。
在本综述中，我们评估了短读段比对器的性能，目的是优化种系变异调用的准确性。我们考察了三种通用短读段比对器（BWA-MEM、Bowtie 2 和 Arioc）与三种种系变异调用器（DeepVariant、FreeBayes 和 GATK HaplotypeCaller）结合的性能。我们讨论了读段比对器的行为，以及这些数据元素与变异调用器所依赖的数据元素之间的关系，并举例说明了这些软件工具的运行时配置如何结合起来影响变异调用性能。
快速的棕色狐狸跳过了懒惰的狗。
