Gene ontology analysis for RNA-seq: accounting for selection bias
Genome biology, 2010•Springer
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 …
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 …
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.
Springer