RASER: reads aligner for SNPs and editing sites of RNA.
BACKGROUND
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.


METHODS
RASER is written in C++ and freely available for download at https://github.com/jaegyoonahn/RASER.
Department of Integrative Biology and Physiology and the Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA 90095, USA.
Jaegyoon
J
Ahn
Department of Integrative Biology and Physiology and the Molecular Biology Institute, University of California Los Angeles, Los Angeles, CA 90095, USA.
Xinshu
X
Xiao
D000465:Algorithms; D000483:Alleles; D020641:Polymorphism, Single Nucleotide; D017393:RNA Editing; D016415:Sequence Alignment / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software