statFDR: FDR control

In eg-r/sights: Statistics and dIagnostic Graphs for HTS

FDR control

Description

Apply Storey's FDR control to p-values

Usage

statFDR(testMatrix, ctrlMethod = "smoother", ...)

Arguments

testMatrix	Data frame or numeric matrix consisting of output from statT or statRVM functions. P-value columns from this matrix are automatically selected for FDR calculation. Columns are samples, and rows are plate wells.
ctrlMethod	Optional. Method to use either 'smoother' or 'bootstrap' to estimate null. Default is 'smoother'.
...	Optional. Additional parameters passed to qvalue function.

Details

False Discovery Rate procedure is used to control the proportion of false positives in the results. This is an implementation of the positive false discovery (pFDR) procedure of the qvalue function.

Value

A matrix of parameters for each replicate group is returned:

T-statistic or RVM T-statistic	Value of the t-statistic.
Mean_Difference	Difference between the calculated and the true mean.
Standard_Error	Standard error of the difference between means.
Degrees_Of_Freedom	Degrees of freedom for the t-statistic.
P-value	P-value for the t-test.
q-value	FDR q-value for the P-value.

Note

Please install the package 'qvalue' from Bioconductor, if not already installed.

References

Storey (2002). A direct approach to false discovery rates. Journal of the Royal Statistical Society: Series B, 64, 479-498.

See Also

Other statistical methods: statRVM, statT

Examples

## load dataset
data(ex_dataMatrix)

## normalize data matrix using any method and store in new variable
ex_normMatrix <- normSights(dataMatrix = ex_dataMatrix, dataCols = 5:10,
normMethod = 'normZ')
## test normalized data matrix using either the RVM or T test and store in new variable
ex_testMatrix <- statT(normMatrix = ex_normMatrix, trueMean = 0,
repIndex = c(1,1,1,2,2,2))
## apply FDR control to test matrix with bootstrap control method
ex_ctrlMatrix <- statFDR(testMatrix = ex_testMatrix,
ctrlMethod = 'bootstrap')

eg-r/sights documentation built on Jan. 28, 2023, 12:17 a.m.