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

被引：0
作者：
Matthew D Young
Matthew J Wakefield
Gordon K Smyth
Alicia Oshlack
机构：
[1] The Walter and Eliza Hall Institute of Medical Research,Bioinformatics Division
来源：
Genome Biology | / 11卷
关键词：
Gene Ontology; Androgen; LNCaP Cell; Differentially Express; Differentially Express Gene;
D O I：
暂无
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学科分类号：
摘要：
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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