To utilize this package, the count matrix coupled with label information
should be stored to a TCC-class object using the new
method.
All functions,
except for two recently added functions (i.e., ROKU
and
WAD
) for microarray data,
used in this package require this TCC-class object.
Using this object, the calcNormFactors
function calculates
normalization factors and the estimateDE
function estimates
the degree of differential expression (DE) for individual genes.
The estimated normalization factors obtained by using the
calcNormFactors
function are used within the statistical
model for differential analysis in the estimateDE
function.
Both two functions internally call functions from other packages
(edgeR, DESeq, baySeq, EBSeq, and samr) when specified.
TCC also provides some useful functions: simulateReadCounts
for generating simulation data with various experimental designs,
plot
for depicting a M-A plot,
plotFCPseudocolor
for depicting a pseudo-color image of
simulation condition that the user specified,
WAD
for identifying DEGs from two-group microarray data
(single-factor design), and ROKU
for identifying
tissue-specific genes from microarray data for many tissues.
data(hypoData)
group <- c(1, 1, 1, 2, 2, 2)
tcc <- new("TCC", hypoData, group)
show(tcc)
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