The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads
Author(s)
Liao, Y; Smyth, GK; Shi, W;
Details
Publication Year 2019-05-07,Volume 47,Issue #8,Page e47
Journal Title
Nucleic Acids Research
Publication Type
Journal Article
Abstract
We present Rsubread, a Bioconductor software package that provides high-performance alignment and read counting functions for RNA-seq reads. Rsubread is based on the successful Subread suite with the added ease-of-use of the R programming environment, creating a matrix of read counts directly as an R object ready for downstream analysis. It integrates read mapping and quantification in a single package and has no software dependencies other than R itself. We demonstrate Rsubread's ability to detect exon-exon junctions de novo and to quantify expression at the level of either genes, exons or exon junctions. The resulting read counts can be input directly into a wide range of downstream statistical analyses using other Bioconductor packages. Using SEQC data and simulations, we compare Rsubread to TopHat2, STAR and HTSeq as well as to counting functions in the Bioconductor infrastructure packages. We consider the performance of these tools on the combined quantification task starting from raw sequence reads through to summary counts, and in particular evaluate the performance of different combinations of alignment and counting algorithms. We show that Rsubread is faster and uses less memory than competitor tools and produces read count summaries that more accurately correlate with true values.
Publisher
Oxford Academic
Research Division(s)
Bioinformatics
PubMed ID
30783653
Open Access at Publisher's Site
https://doi.org/10.1093/nar/gkz114
Terms of Use/Rights Notice
Refer to copyright notice on published article.


Creation Date: 2019-03-13 11:54:07
Last Modified: 2019-06-26 09:27:34
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