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BioMed Central, Genome Biology, 2(11), p. R14

DOI: 10.1186/gb-2010-11-2-r14

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Gene ontology analysis for RNA-seq: accounting for selection bias

Journal article published in 2010 by Matthew D. Young, Matthew J. Wakefield ORCID, Gordon K. Smyth ORCID, Alicia Oshlack
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract We present GOseq, an application for performing Gene Ontology (GO) analysis on RNA-seq data. GO analysis is widely used to reduce complexity and highlight biological processes in genome-wide expression studies, but standard methods give biased results on RNA-seq data due to over-detection of differential expression for long and highly expressed transcripts. Application of GOseq to a prostate cancer data set shows that GOseq dramatically changes the results, highlighting categories more consistent with the known biology.