maigesPack (version 1.36.0)

kmeansM: Function to do k-means cluster analysis

Description

This is a function to do k-means clustering analysis for objects of classes maiges, maigesRaw and maigesANOVA. Use the function kmeansMde for objects of class maigesDEcluster.

Usage

kmeansM(data, group=c("C", "R")[1], distance="correlation", method="complete", sampleT=NULL, doHier=FALSE, sLabelID="SAMPLE", gLabelID="GeneName", rmGenes=NULL, rmSamples=NULL, rmBad=TRUE, geneGrp=NULL, path=NULL, ...)

Arguments

data

object of class maigesRaw, maiges or maigesANOVA.

group

character string giving the type of grouping: by rows 'R' or columns 'C' (default).

distance

char string giving the type of distance to use. Here we use the function Dist and the possible values are 'euclidean', 'maximum', 'manhattan', 'canberra', 'binary', 'pearson', 'correlation' (default) and 'spearman'.

method

char string specifying the linkage method for the hierarchical cluster. Possible values are 'ward', 'single', 'complete' (default), 'average', 'mcquitty', 'median' or 'centroid'

sampleT

list with 2 vectors. The first one specify the first letter of different sample types to be coloured by distinct colours, that are given in the second vector. If NULL (default) no colour is used.

doHier

logical indicating if you want to do the hierarchical branch in the opposite dimension of clustering. Defaults to FALSE.

sLabelID

character string specifying the sample label ID to be used to label the samples.

gLabelID

character string specifying the gene label ID to be used to label the genes.

rmGenes

char list specifying genes to be removed.

rmSamples

char list specifying samples to be removed.

rmBad

logical indicating to remove or not bad spots (slot BadSpots in objects of class maiges, maigesRaw or maigesANOVA).

geneGrp

numerical or character specifying the gene group to be clustered. This is given by the columns of the slot GeneGrps in objects of classes maiges, maigesRaw and maigesANOVA.

path

numerical or character specifying the gene network to be clustered. This is given by the items of the slot Paths in objects of classes maiges, maigesRaw and maigesANOVA.

...

additional parameters for Kmeans function.

Value

This function display the heatmaps and return invisibly a list resulted from the function Kmeans.

Details

This function implements the k-means clustering method for objects of microarray data defined in this package. The method uses the function Kmeans from package amap.

See Also

Kmeans from package amap. somM and hierM for displaying SOM and hierarchical clusters, respectively.

Examples

## Loading the dataset
data(gastro)

## Doing a K-means cluster with 2 groups using all genes, for maigesRaw class
kmeansM(gastro.raw, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
        sLabelID="Sample", gLabelID="Name", centers=2)

## The same as above, but for maigesNorm class
kmeansM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
        sLabelID="Sample", gLabelID="Name", centers=2)

## Another example with 3 groups
kmeansM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
        sLabelID="Sample", gLabelID="Name", centers=3)

## If you want to use euclidean distance to group genes (or spots) with
## 4 groups
kmeansM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
        sLabelID="Sample", gLabelID="Name", centers=4, group="R", distance="euclidean")