Gene ontology analysis for RNA-seq: accounting for selection bias
Walter and Eliza Hall Institute of Medical Research
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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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4Topics & keywords
Topics
Keywords
- Biology
- RNA-Seq
- Gene ontology
- Human genetics
- Computational biology
- Genetics
- Selection (genetic algorithm)
- Gene
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