Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads.
BACKGROUND
Next-generation sequencing of cellular RNA (RNA-seq) is rapidly becoming the cornerstone of transcriptomic analysis. However, sequencing errors in the already short RNA-seq reads complicate bioinformatics analyses, in particular alignment and assembly. Error correction methods have been highly effective for whole-genome sequencing (WGS) reads, but are unsuitable for RNA-seq reads, owing to the variation in gene expression levels and alternative splicing.


RESULTS
We developed a k-mer based method, Rcorrector, to correct random sequencing errors in Illumina RNA-seq reads. Rcorrector uses a De Bruijn graph to compactly represent all trusted k-mers in the input reads. Unlike WGS read correctors, which use a global threshold to determine trusted k-mers, Rcorrector computes a local threshold at every position in a read.


CONCLUSIONS
Rcorrector has an accuracy higher than or comparable to existing methods, including the only other method (SEECER) designed for RNA-seq reads, and is more time and memory efficient. With a 5 GB memory footprint for 100 million reads, it can be run on virtually any desktop or server. The software is available free of charge under the GNU General Public License from https://github.com/mourisl/Rcorrector/.
Department of Computer Science, Johns Hopkins University, Baltimore, 21218 USA.
Li
L
Song
Department of Computer Science, Johns Hopkins University, Baltimore, 21218 USA ; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, 21205 USA.
Liliana
L
Florea
D012313:RNA / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*
D012313:RNA
Error correction; Next-generation sequencing; RNA-seq; k-mers