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.
Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville 3052, Australia.
Matthew D
MD
Young
Matthew J
MJ
Wakefield
Gordon K
GK
Smyth
Alicia
A
Oshlack
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