Count-based differential expression analysis of RNA sequencing data using R and Bioconductor-Reference-Cited by-同舟云学术

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Count-based differential expression analysis of RNA sequencing data using R and Bioconductor

Published:2013-08-22 Issue:9 Volume:8 Page:1765-1786
ISSN:1754-2189
Container-title:Nature Protocols
language:en
Short-container-title:Nat Protoc

Author:

Anders Simon,McCarthy Davis J,Chen Yunshun,Okoniewski Michal,Smyth Gordon K,Huber Wolfgang,Robinson Mark D

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology

Link

http://www.nature.com/articles/nprot.2013.099.pdf

Reference66 articles.

1. Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat. Methods 5, 621–628 (2008).

2. Wang, Z., Gerstein, M. & Snyder, M. RNA-seq: a revolutionary tool for transcriptomics. Nat. Rev. Genet. 10, 57–63 (2009).

3. Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).

4. Robinson, M.D. & Smyth, G.K. Moderated statistical tests for assessing differences in tag abundance. Bioinformatics 23, 2881–2887 (2007).

5. Robinson, M.D. & Smyth, G.K. Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics 9, 321–332 (2008).

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