somM {maigesPack} | R Documentation

## Function to do SOM cluster analysis

### Description

This is a function to do SOM (Self Organising Maps) clustering analysis for objects of classes `maiges`, `maigesRaw` and `maigesANOVA`. Use the function `somMde` for objects of class `maigesDEcluster`.

### Usage

    somM(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. Only two options are available here: 'euclidean' and 'correlation' (default).
`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 `som` function.

### Details

This function implements the SOM clustering method for objects of microarray data defined in this package. The method uses the function `som` from package som.

### Value

This function display the heatmaps and return invisibly an object of class `som` resulted from the function `som`.

### Author(s)

Gustavo H. Esteves <gesteves@vision.ime.usp.br>

### See Also

`som` from package som. `kmeansM` and `hierM` for displaying k-means and hierarchical clusters, respectively.

### Examples

    ## Loading the dataset
    data(gastro)

    ## Doing a SOM cluster with 2 groups using all genes, for maigesRaw class
    somM(gastro.raw, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
         sLabelID="Sample", gLabelID="Name", xdim=2, ydim=1, topol="rect")

    ## Doing a SOM cluster with 3 groups using all genes, for maigesNorm class
    somM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
         sLabelID="Sample", gLabelID="Name", xdim=3, ydim=1, topol="rect")

    ## Another example with 4 groups
    somM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
         sLabelID="Sample", gLabelID="Name", xdim=2, ydim=2, topol="rect")

    ## If you want to use euclidean distance to group genes (or spots), with
    ## 3 groups
    somM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
         sLabelID="Sample", gLabelID="Name", group="R",
         distance="euclidean", xdim=3, ydim=1, topol="rect")

[Package maigesPack version 1.8.0 Index]