Voom: precision weights unlock linear model analysis tools for RNA-seq read counts
Details
Publication Year 2014-02-03, Volume 15, Issue #2, Page R29
Journal Title
Genome Biology
Publication Type
Journal Article
Abstract
Normal linear modeling methods are developed for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation, and then enters these into a limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.
Publisher
BioMed Central
WEHI Research Division(s)
Bioinformatics
Link To PubMed Central Version
http://www.ncbi.nlm.nih/pmc/articles/PMC4053721/
Rights Notice
© 2014 Law et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.


Creation Date: 2014-07-10 09:26:33
Last Modified: 0001-01-01 12:00:00
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