statT: t-test
In sights: Statistics and dIagnostic Graphs for HTS

Description Usage Arguments Details Value See Also Examples

Apply one-sample t-test separately to each plate

1 2	statT(normMatrix, repIndex, normRows = NULL, normCols = NULL, testSide = "two.sided", trueMean = 0)

`normMatrix`	Data frame or numeric matrix of normalized data. Columns are plates, and rows are plate wells.
`repIndex`	Integer vector indicating replicates in normMatrix. Which plates are replicates of each other? Provide the same number for plates belonging to a replicate group. Each index in the vector matches the corresponding column of normMatrix.
`normRows, normCols`	Optional integer vector. Indicate which row/column numbers from the normMatrix should be tested. If NULL then all rows/columns from the normMatrix are used.
`testSide`	Optional. Type of t-test: 'two.sided', 'less', or 'greater'. Default is 'two.sided'.
`trueMean`	Optional. Number indicating true value of mean. Default is 0.

Standard one-sample t-test is applied to the normalized data.

A matrix of parameters for each replicate group is returned:

`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.

Other statistical methods: statFDR, statRVM

## 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')
## apply T test to normalized data matrix and get the p-values
ex_testMatrix <- statT(normMatrix = ex_normMatrix, trueMean = 0,
repIndex = c(1,1,1,2,2,2))