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
- Research Division(s)
- Bioinformatics
- Link To PubMed Central Version
- http://www.ncbi.nlm.nih/pmc/articles/PMC4053721/
- Publisher's Version
- https://doi.org/10.1186/gb-2014-15-2-r29
- Terms of Use/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