findSigLevelTrad {KCsmart} | R Documentation |
Method to find the cutoff at which gains and losses are considered significant using permutations
findSigLevelTrad(data, observedSpm, n = 1, p = 0.05, maxmem = 1000)
data |
aCGH data in the same format as used for 'calcSpm' |
observedSpm |
A sample point matrix as produced by 'calcSpm' |
n |
Number of permutations |
p |
Alpha level for significance |
maxmem |
This parameter controls memory usage, set to lower value to lower memory consumption |
The number of permutations needed for reliable results depends on the data and can not be determined beforehand. As a general rule-of-thumb around 100 permutations should be used for 'quick checks' and around 2000 permutations for more rigorous testing.
p is the uncorrected alpha level, the method corrects for multiple testing internally using simple Bonferroni correction. See the referenced publication for more details.
A list with the cutoffs corresponding to the given alpha level
pos |
The cutoff for the gains |
neg |
The cutoff for the losses' |
Jorma de Ronde
data(hsSampleData) data(hsMirrorLocs) spm1mb <- calcSpm(hsSampleData, hsMirrorLocs) sigLevel1mb <- findSigLevelTrad(hsSampleData, spm1mb, n=3) plot(spm1mb, sigLevels=sigLevel1mb) plotScaleSpace(list(spm1mb), list(sigLevel1mb), type='g')