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

Mark D. Robinson; Alicia Oshlack · Genome biology · 2010

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Author / responsible party
Mark D. Robinson; Alicia Oshlack
Publisher
Genome biology
Year
2010
Language
English

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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.

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APA 7

Robinson, M. D. & Oshlack, A. (2010). A scaling normalization method for differential expression analysis of RNA-seq data. https://doi.org/10.1186/gb-2010-11-3-r25

MLA

Robinson, Mark D, and Alicia Oshlack. "A scaling normalization method for differential expression analysis of RNA-seq data." 2010. https://doi.org/10.1186/gb-2010-11-3-r25.

Chicago

Robinson, Mark D. and Alicia Oshlack. 2010. "A scaling normalization method for differential expression analysis of RNA-seq data.". https://doi.org/10.1186/gb-2010-11-3-r25.

Harvard

Robinson, M. D. and Oshlack, A. 2010, A scaling normalization method for differential expression analysis of RNA-seq data, Genome biology, available at: https://doi.org/10.1186/gb-2010-11-3-r25 [Accessed 8 Aug. 2026].

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Title
A scaling normalization method for differential expression analysis of RNA-seq data
Author / contributors
Mark D. Robinson; Alicia Oshlack
Publisher
Genome biology
Publication year
2010
Language
English

Subjects

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Biology; Normalization (sociology); RNA-Seq; Computational biology; Human genetics; Computational genomics; Genetics; RNA; Evolutionary biology; Gene expression; Genomics; Transcriptome
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