Gene ontology analysis for RNA-seq: accounting for selection bias View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-02

AUTHORS

Matthew D Young, Matthew J Wakefield, Gordon K Smyth, Alicia Oshlack

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. More... »

PAGES

r14

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/gb-2010-11-2-r14

DOI

http://dx.doi.org/10.1186/gb-2010-11-2-r14

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1050171830

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20132535


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