Description Usage Arguments Value References Examples
This function analyzes RFI RNA-seq data and simulated datasets using
voom
, which uses precision weights and linear model
pipeline for the analysis of log-transformed RNA-seq data.
1 | voomlimmaFit(counts, design, Effect)
|
counts |
a matrix of count data. |
design |
a design matrix. |
Effect |
the effect used to simulate data, either line2, or time. This effect is considered as the main factor of interest where the status of DE and EE genes was specified. |
a list of 4 components
fit |
output of voom-limma fit. |
pv |
a vector of p-values of the test for significant of
|
qv |
a vector of q-values corresponding to the
|
1. Gordon K. Smyth, Matthew Ritchie, Natalie Thorne,James Wettenhall, Wei Shi and Yifang Hu. limma: Linear Models for Microarray and RNA-Seq Data. User's Guide. https://www.bioconductor.org/packages/devel/bioc/vignettes/limma/inst/doc/usersguide.pdf
2. Gordon K. Smyth. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2004;3:Article3. Epub 2004 Feb 12.
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