Ontology type: schema:ScholarlyArticle Open Access: True
2010-02
AUTHORSMatthew D Young, Matthew J Wakefield, Gordon K Smyth, Alicia Oshlack
ABSTRACTWe 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... »
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DOIhttp://dx.doi.org/10.1186/gb-2010-11-2-r14
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PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/20132535
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