Gene ontology analysis for RNA-seq: accounting for selection bias.
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.
Young
Matthew D
MD
Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville 3052, Australia.
Wakefield
Matthew J
MJ
Smyth
Gordon K
GK
Oshlack
Alicia
A
D000728:Androgens / Q000494:pharmacology; D015982:Bias; D045744:Cell Line, Tumor; D015972:Gene Expression Regulation, Neoplastic; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*
D000728:Androgens