# comp.t: Computing One and Two Sample t-statistic for Differential... In Bioconductor-mirror/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

 `1` ```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, [email protected],
Jean Yee Hwa Yang, [email protected].

`comp.FC`, `comp.F`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```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) ```