comp.t: Computing One and Two Sample t-statistic for Differential...

In DEDS: Differential Expression via Distance Summary for Microarray Data

Description

comp.t returns a function of one argument with bindings for L, mu, var.equal. This function accepts a microarray data matrix as its single argument, when evaluated, computes t statistics for each row of the matrix.

Usage

comp.t(L = NULL, mu = 0, var.equal = FALSE)

Arguments

L	A vector of integers corresponding to observation (column) class labels. For k classes, the labels must be integers between 0 and k-1.
mu	A number indicating the true value of the mean (or difference in means if you are performing a two sample test).
var.equal	a logical variable indicating whether to treat the two variances as being equal. If TRUE then the pooled variance is used to estimate the variance otherwise the Welch statistic will be calculated.

Details

The function returned by comp.t calculates t statistics for each row of the microarary data matrix, given specific class labels.

Value

comp.t returns a function with bindings for L, mu, var.equal, which calculates and returns of vector of t statistics for each row in the data matrix.

Author(s)

Yuanyuan Xiao, [e-mail],
Jean Yee Hwa Yang, [e-mail].

See Also

comp.FC, comp.F

Examples

X <- matrix(rnorm(1000,0,0.5), nc=10)
L <- rep(0:1,c(5,5))

# genes 1-10 are differentially expressed
X[1:10,6:10]<-X[1:10,6:10]+1

# two sample test, unequal variance
t.fun <- comp.t(L)
t.X <- t.fun(X)

# two sample test, equal variance
t.fun <- comp.t(L, var.equal=TRUE)
t.X <- t.fun(X)

DEDS documentation built on Oct. 31, 2019, 3:15 a.m.