Abstract

Motivation: RNA sequencing is becoming a standard for expression profiling experiments and many tools have been developed in the past few years to analyze RNA-Seq data. Numerous 'Bioconductor' packages are available for next-generation sequencing data loading in R, e. g. ShortRead and Rsamtools as well as to perform differential gene expression analyses, e. g. DESeq and edgeR. However, the processing tasks lying in between these require the precise interplay of many Bioconductor packages, e. g. Biostrings, IRanges or external solutions are to be sought.Results: We developed 'easyRNASeq', an R package that simplifies the processing of RNA sequencing data, hiding the complex interplay of the required packages behind a single functionality.

Published in

Bioinformatics
2012, Volume: 28, number: 19, pages: 2532-2533
Publisher: OXFORD UNIV PRESS

UKÄ Subject classification

Bioinformatics and Systems Biology
Bioinformatics (Computational Biology)


Publication identifier

DOI: https://doi.org/10.1093/bioinformatics/bts477

Permanent link to this page (URI)

https://res.slu.se/id/publ/80799