Journal article
Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation
Davis J McCarthy, Yunshun Chen, Gordon K Smyth
NUCLEIC ACIDS RESEARCH | OXFORD UNIV PRESS | Published : 2012
DOI: 10.1093/nar/gks042
Abstract
A flexible statistical framework is developed for the analysis of read counts from RNA-Seq gene expression studies. It provides the ability to analyse complex experiments involving multiple treatment conditions and blocking variables while still taking full account of biological variation. Biological variation between RNA samples is estimated separately from the technical variation associated with sequencing technologies. Novel empirical Bayes methods allow each gene to have its own specific variability, even when there are relatively few biological replicates from which to estimate such variability. The pipeline is implemented in the edgeR package of the Bioconductor project. A case study a..
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Awarded by National Health and Medical Research Council
Funding Acknowledgements
National Health and Medical Research Council (Program Grant 490036 and Research Fellowship to G.K.S.); Autralian Government (Australian Postgraduate Research Award to Y.C.). Funding for open access charge: National Health and Medical Research Council Program Grant 490036.