maanova (version 1.42.0)

fom: Figure of Merit

Description

K-means clustering needs a given number of groups, which is difficult to guess in most of the cases. This function calculates the Figure of Merit values for different number of groups and generates the FOM plot (FOM value versus number of groups). Lower FOM value means better grouping. User can decide the number of groups in kmeans cluster based on that result.

Usage

fom(anovaobj, idx.gene, term, ngroups)

Arguments

anovaobj

An object of class maanova.

idx.gene

The index of genes to be clustered.

term

The factor (in formula) used in clustering. The expression level for this term will be used in clustering. This term has to correspond to the gene list, e.g, idx.gene in this function. The gene list should be the significant hits in testing this term.

ngroups

The number of groups for K-means cluster. This could be a vector or an integer.

Value

A vector of FOM values for the given number of groups

References

Yeung, K.Y., D.R. Haynor, and W.L.Ruzzo (2001). Validating clustering for gene expression data. Bioinformatics, 17:309-318.

See Also

macluster, consensus, kmeans

Examples

# load in data
data(abf1)
# fit the anova model
## Not run: 
# fit.fix = fitmaanova(abf1,formula = ~Strain)
# # test Strain effect 
# test.fix = matest(abf1, fit.fix, term="Strain",n.perm= 1000)
# # pick significant genes - pick the genes selected by Fs test
# idx <- volcano(test.fix)$idx.Fs
# # generate FOM
# m <- fom(fit.fix, idx, "Strain", 10)## End(Not run)