article Open AccessTop 1% cited
A scaling normalization method for differential expression analysis of RNA-seq data
Genome biology · 2010 · Vol. 11(3) · pp. R25–R25
Mark D. Robinson✉(Walter and Eliza Hall Institute of Medical Research)Alicia Oshlack(Walter and Eliza Hall Institute of Medical Research)
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.
Cancer-related molecular mechanisms researchRNA Research and SplicingRNA modifications and cancerBiologyNormalization (sociology)RNA-SeqComputational biologyHuman geneticsComputational genomicsGeneticsRNAEvolutionary biologyGene expression
MeSH terms
Base SequenceComputer SimulationRNAModels, StatisticalGene LibraryGene Expression Profiling
Funding
- Medical Research Council
- National Health and Medical Research Council
Citations
8,395
FWCI
38.33
field-weighted impact
References
28
Percentile
100%
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Citations per year
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