KCsmart Comparative calculate null distribution

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Description

Compare the samples of one class in the sample point matrix collection to the samples in the other class and calculate the null distribution

Usage

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compareSpmCollection(spmCollection, nperms=20, method=c("siggenes", "perm"), siggenes.args=NULL, altcl=NULL)

Arguments

spmCollection

An spmCollection object as created by the 'calcSpmCollection' function

nperms

The number of permutations to be used to calculate the null distribution

altcl

Instead of using the class vector from the spmCollection object an alternative vector can be used

method

The method to be used to calculate the null distribution

siggenes.args

Optional additional arguments to the siggenes function

Details

The method to be used to determine significant regions can either be the SAM methodology from the siggenes package or a signal-to-noise/permutation based method. For more information regarding the siggenes method please check the corresponding package.

Value

Returns a compKc object which returns the original data and, depending on the method used, the permuted data or the fdr-delta value combinations as calculated by the siggenes package.

Author(s)

Jorma de Ronde

See Also

compareSpmCollection, getSigRegionsCompKC

Examples

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data(hsSampleData)
data(hsMirrorLocs)

spmc1mb <- calcSpmCollection(hsSampleData, hsMirrorLocs, cl=c(rep(0,10),rep(1,10)))
spmcc1mb <- compareSpmCollection(spmc1mb, nperms=3)
spmcc1mbSigRegions <- getSigRegionsCompKC(spmcc1mb)

plot(spmcc1mb, sigRegions=spmcc1mbSigRegions)