Description Usage Arguments Value Examples
To avoid unnecessary computational burdens and noises, pre-screening is an
essential step. This screening process consists of three steps:
step 1
step 2
step 3
1 | DeMix.Filter(input.mat, design, zerofilter=TRUE, conc=0.8, fc=1.2)
|
input.mat |
numeric matrix of gene expressions after normalization.
The |
design |
integer vector of |
zerofilter |
logical scalar. If |
conc |
numeric scalar cut-off value used for checking the linearity assumption. More than 0.8 or 80% is recommended. |
fc |
numeric scalar fold-change cut-off value used for identifying informative genes in proportion estimations. 1.2 or 1/1.2 is default. This value needs to be set for reducing data-size. Approximately 2,000-3,000 genes/probes will provide robust estimates. |
Returns numeric G'*S} matrix of gene expressions after the prescreening,
where \code{G'
is the number of remaining genes and S
is the number
of samples.
1 2 3 4 5 6 7 | data(ntot_NT_Liver)
# First 50 samples normal, remaining 151 tumor for this dataset
input.mat <- as.matrix(ntot_NT_Liver.df)
design <- c(rep(0, 50),
rep(1, 151))
filtered.mat <- DeMix:::DeMix.Filter(input.mat, design)
|
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