voom: precision weights unlock linear model analysis tools for RNA-seq read counts View Full Text


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Article Info

DATE

2014-02-03

AUTHORS

Charity W Law, Yunshun Chen, Wei Shi, Gordon K Smyth

ABSTRACT

New normal linear modeling strategies are presented 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 enters these into the 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. More... »

PAGES

r29

References to SciGraph publications

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  • Journal

    TITLE

    Genome Biology

    ISSUE

    2

    VOLUME

    15

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/gb-2014-15-2-r29

    DOI

    http://dx.doi.org/10.1186/gb-2014-15-2-r29

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1045312009

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/24485249


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