A scaling normalization method for differential expression analysis of RNA-seq data.

Genome Biology
Mark D Robinson, Alicia Oshlack

Abstract

The fine detail provided by sequencing-based transcriptome surveys suggests that RNA-seq is likely to become the platform of choice for interrogating steady state RNA. In order to discover biologically important changes in expression, we show that normalization continues to be an essential step in the analysis. We outline a simple and effective method for performing normalization and show dramatically improved results for inferring differential expression in simulated and publicly available data sets.

Associated Clinical Trials

References

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Citations

Sep 6, 2013·Acta Neuropathologica·Katja KobowIngmar Blümcke
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Methods Mentioned

BETA
RNA-seq
immunoprecipitation
ChIP

Software Mentioned

llumina 1G Genome Analyzer
CRAN statmod
Ensembl
PeakSeq
biomaRt package
R
Bioconductor
edgeR

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