Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads
Johns Hopkins University · Johns Hopkins Medicine
Abstract
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.
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.
Citation impact
- FWCI
- 9.94
- Percentile
- 100%
- References
- 26
Authors
2Topics & keywords
- Computer science
- Computational biology
- RNA-Seq
- Data mining
- Biology
- Genetics
- Transcriptome
- Gene