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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-03-02

AUTHORS

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. More... »

PAGES

r25

Journal

TITLE

Genome Biology

ISSUE

3

VOLUME

11

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/gb-2010-11-3-r25

DOI

http://dx.doi.org/10.1186/gb-2010-11-3-r25

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1050509557

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20196867


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