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

Matthew D. Young; Matthew J. Wakefield; Gordon K. Smyth; Alicia Oshlack · Genome biology · 2010

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Matthew D. Young; Matthew J. Wakefield; Gordon K. Smyth; Alicia Oshlack

Publisher

Genome biology

Year

2010

Language

English

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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.

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APA 7

Young, M. D, Wakefield, M. J, Smyth, G. K, & Oshlack, A. (2010). Gene ontology analysis for RNA-seq: accounting for selection bias. https://doi.org/10.1186/gb-2010-11-2-r14

MLA

Young, Matthew D, et al. "Gene ontology analysis for RNA-seq: accounting for selection bias." 2010. https://doi.org/10.1186/gb-2010-11-2-r14.

Chicago

Young, Matthew D, Matthew J. Wakefield, Gordon K. Smyth, and Alicia Oshlack. 2010. "Gene ontology analysis for RNA-seq: accounting for selection bias.". https://doi.org/10.1186/gb-2010-11-2-r14.

Harvard

Young, M. D. et al. 2010, Gene ontology analysis for RNA-seq: accounting for selection bias, Genome biology, available at: https://doi.org/10.1186/gb-2010-11-2-r14 [Accessed 9 Aug. 2026].

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

Author / contributors: Matthew D. Young; Matthew J. Wakefield; Gordon K. Smyth; Alicia Oshlack

Publisher: Genome biology

Publication year: 2010

Language: English

Subjects

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Biology; RNA-Seq; Gene ontology; Human genetics; Computational biology; Genetics; Selection (genetic algorithm); Gene; Genome Biology; Ontology; Evolutionary biology; Genomics