RASER: reads aligner for SNPs and editing sites of RNA

• DOI: 10.1093/bioinformatics/btv505
• Publication Date: 2015-09-01T00:34:13Z
• Authors: Jaegyoon Ahn; Xinshu Xiao
• Keywords: Bioinformatics; 0206 medical engineering; Bioinformatics and Computational Biology; 610; Mathematical sciences; 02 engineering and technology; Polymorphism, Single Nucleotide; Mathematical Sciences; Information and Computing Sciences; Genetics; Polymorphism; Alleles; Sequence Analysis, RNA; Single Nucleotide; Biological Sciences; 620; Biological sciences; Information and computing sciences; RNA; RNA Editing; Sequence Analysis; Sequence Alignment; Algorithms; Software

Abstract Motivation: Accurate identification of genetic variants such as single-nucleotide polymorphisms (SNPs) or RNA editing sites from RNA-Seq reads is important, yet challenging, because it necessitates a very low false-positive rate in read mapping. Although many read aligners are available, no single aligner was specifically developed or tested as an effective tool for SNP and RNA editing prediction. Results: We present RASER, an accurate read aligner with novel mapping schemes and index tree structure that aims to reduce false-positive mappings due to existence of highly similar regions. We demonstrate that RASER shows the best mapping accuracy compared with other popular algorithms and highest sensitivity in identifying multiply mapped reads. As a result, RASER displays superb efficacy in unbiased mapping of the alternative alleles of SNPs and in identification of RNA editing sites. Availability and implementation: RASER is written in C++ and freely available for download at https://github.com/jaegyoonahn/RASER. Contact: [e-mail] Supplementary information: Supplementary data are available at Bioinformatics online.