compareSpmCollection {KCsmart} | R Documentation |
Compare the samples of one class in the sample point matrix collection to the samples in the other class and calculate the null distribution
compareSpmCollection(spmCollection, nperms=20, method=c("siggenes", "perm"), siggenes.args=NULL, altcl=NULL)
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 |
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.
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.
Jorma de Ronde
compareSpmCollection
, getSigRegionsCompKC
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)