Gene ontology analysis for RNA-seq: accounting for selection bias |
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Authors: | Matthew D Young Matthew J Wakefield Gordon K Smyth Alicia Oshlack |
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Affiliation: | (1) Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, 3052, Australia |
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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. |
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