MiStatCount: FDR for microarray gene expression data
In MiDA: Microarray Data Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Performs descriptive statistics and FDR (False Discovery Rate) test for microarray expression matrix

1	MiStatCount(Matrix, specimens)

`Matrix`	numeric matrix of expression data where each row corresponds to a probe (gene, transcript), and each column correspondes to a specimen (patient).
`specimens`	factor vector with two levels specifying specimens in the columns of the `Matrix`.

This function takes matrix of expression data and performs T-test with FDR correction for two groups for each probe.
T-test is a two-sided, two-class with equal variances against the null hypothesis 'mean1=mean2' for each row. See rowttests for details.

a data frame containing for each probe: mean and sd values for both groups, difference of means, p-value for T-test and q-value for FDR (False Discovery Rate) correction.

Elena N. Filatova

Welch B.L.(1951) On the comparison of several mean values: an alternative approach. Biometrika 38, 330-336. https://doi.org/10.1093/biomet/38.3-4.330

rowttests

data("IMexpression"); data("IMspecimen") # load data and specimen information
#sampling data and specimen information
ExpData<-MiDataSample(IMexpression, IMspecimen$diagnosis,"ebv", "norm")
Specimens<-MiSpecimenSample(IMspecimen$diagnosis, "ebv", "norm")
#Counting statistics
StatRes<-MiStatCount(ExpData, Specimens)
head(StatRes)