deds.chooseTest: Selection of the Most Common Statistics for Differential...

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/DEDS.R

Description

This function selects a set of functions of common statistics for differential expression in microarray data analysis, given specific observation class labels. As a default, t-statistics, fold change and SAM are selected.

Usage

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deds.chooseTest(L = NULL, tests = c("t", "sam", "fc"))

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.

tests

A character vector specifying the statistics to be used to test the null hypothesis of no association between the variables and the class labels. For DEDS, there should be more than one statistic chosen from the following:

"t": t-statistics;
"f": F-statistics;
"fc": fold changes;
"sam": SAM-statistics;
"modt": moderated t-statistics;
"modf": moderated F-statistics;
"B": B-statistics.

Details

deds.chooseTest can be used together with the function deds.stat. The user specifies the types of statistics needed for subsequent DEDS analysis by the argument tests and the function returns accordingly a list the statistics function, which could be used for input testfun in the function deds.stat.

Value

A list of statistics functions specified by the user which could be used for input in the function deds.stat.

Author(s)

Yuanyuan Xiao, [email protected],
Jean Yee Hwa Yang, [email protected].

See Also

comp.t, comp.FC, comp.SAM

Examples

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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

# as a default, chooses t, fc and sam
funcs <- deds.chooseTest(L)
deds.X <- deds.stat(X, L, testfun=funcs)

# chooses F statistic, SAM statistic, and moderated F statistic
L <- rep(0:2, c(3,3,4))
funcs <- deds.chooseTest(L, tests=c("f", "sam", "modf"))

Bioconductor-mirror/DEDS documentation built on June 1, 2017, 5:11 p.m.