voomlimmaFit: Analysis of RFI RNA-seq data Using voom
Description
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.
Usage
voomlimmaFit(counts, design, Effect)
Arguments
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.
Value
a list of 4 components
fit
output of voom-limma fit.
pv
a vector of p-values of the test for significant of
Effect.
qv
a vector of q-values corresponding to the
pv above.
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.