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. 2019 May 7;47(8):e47.
doi: 10.1093/nar/gkz114.

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

Yang Liao  1   2 , Gordon K Smyth  1   3 , Wei Shi  1   4
Affiliations

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

Yang Liao et al. Nucleic Acids Res. .

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.

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Figures

Figure 1.
Figure 1.
Run times of read aligners. Each aligner used ten threads to map 15 million 100 bp read-pairs from the SEQC UHRR sample to the human reference genome GRCh38. Rsubread::align is faster than STAR or TopHat2 regardless of whether the full index (align-F) or a gapped index (align-G) is used.
Figure 2.
Figure 2.
Running time of different quantification tools. Labels under each bar indicate the quantification method and the aligner (in parenthesis) that produced the mapped reads used for counting. Mapped reads were assigned to NCBI RefSeq human genes. featureCounts is the only tool that supports multi-threaded read counting and it was run with four threads.
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