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.
A vector of integers corresponding to observation (column) class labels. For k classes, the labels must be integers between 0 and k-1.
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:
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
A list of statistics functions specified by the user which could be
used for input in the function
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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"))
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