RandAL: A randomized approach to aligning DNA sequences to reference genomes

Abstract

Background: The alignment of short reads generated by next-generation sequencers to genomes is an important problem in many biomedical and bioinformatics applications. Although many proposed methods work very well on narrow ranges of read lengths, they tend to suffer in performance and alignment quality for reads outside of these ranges. Results: We introduce RandAL, a novel method that aligns DNA sequences to reference genomes. Our approach utilizes two FM indices to facilitate efficient bidirectional searching, a pruning heuristic to speed up the computing of edit distances, and most importantly, a randomized strategy that enables effective estimation of key parameters. Extensive comparisons showed that RandAL outperformed popular aligners in most instances and was unique in its consistent and accurate performance over a wide range of read lengths and error rates. The software package is publicly available at https://github.com/namsyvo/RandAL. Conclusions: RandAL promises to align effectively and accurately short reads that come from a variety of technologies with different read lengths and rates of sequencing error.