orQA (version 0.2.1)

pttest: Perform permutation t-tests between consecutive levels of ordered groups

Description

This function computes permutation t-tests for differences in each line of a matrix between consecutive levels of an ordered grouping variable.

Usage

pttest(data,g,B,rep=rep(1,length(g)))

Arguments

data

a numeric matrix, for the lines of which we want to test the null of no trend across groups

g

integer vector with group labels for the ordered categories coded as integers between 1 and n, where n is the number of ordered categories

B

number of permutations or a list of permutation matrices

rep

integer vector with group labels ranging from 1 to m where m is the number of independent samples (e.g. individuals). The ordering is not important.

Value

raw

matrix with raw p.values

dir

matrix with the direction of each decision

Details

pttest takes a matrix and for each line computes a permutation t-test between consecutive levels of an ordered grouping variable. Random factors e.g. technical replicates can be specified and will be accounted for by permuting samples only within independent units of this factor. A matrix with raw permutation p-values as well as a matrix with the directional decisions are returned. See guo and sigdirPttestfor a way to get test decisions with control over the mixed directional false discovery rate.

References

Klinglmueller, F., Tuechler, T., Posch, M. (2010) "Cross Platform Comparison Of Microarray Data Using Order Restricted Inference" Under Review

Guo W., Sarkar SK., Peddada SD. (2010) "Controlling False Discoveries in Multidimensional Directional Decisions, with Applications to Gene Expression Data on Ordered Categories" Biometrics

Examples

data <- matrix(rnorm(7200),nc=72)
groups <- rep(1:4,each=18)
ind <- rep(rep(1:3,each=6),4)
out <- pttest(data,groups,B=1000,rep=ind)
guo(out$unadj,.05)
data2 <- data+matrix(rep(groups,nrow(data)),nr=nrow(data),byrow=TRUE)
out2 <- pttest(data2,groups,B=1000,rep=ind)
guo(out2$unadj,.05)