hierM {maigesPack} | R Documentation

## Function to do hierarchical cluster analysis

### Description

This is a function to do hierarchical clustering analysis for objects of classes `maiges`, `maigesRaw` and `maigesANOVA`. Use the function `hierMde` for objects of class `maigesDEcluster`.

### Usage

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

### Arguments

`data` | object of class `maigesRaw`, `maiges`, `maigesANOVA` or `maigesDEcluster`.
`group` | character string giving the type of grouping: by rows 'R', columns 'C' (default) or both 'B'.
`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'
`doHeat` | logical indicating to do or not the heatmap. If FALSE, only the dendrogram is displayed.
`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 `heatmap` function.

### Details

This function implements the hierarchical clustering method for objects of microarray data defined in this package. The default function for hierarchical clustering is the `hclust`.

### Value

This function display the heatmaps and don't return any object or value.

### Author(s)

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

### See Also

`somM` and `kmeansM` for displaying SOM and k-means clusters, respectively.

### Examples

    ## Loading the dataset
    data(gastro)

    ## Doing a hierarchical cluster using all genes, for maigesRaw class
    hierM(gastro.raw, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
          sLabelID="Sample", gLabelID="Name", doHeat=FALSE)

    ## Doing a hierarchical cluster using all genes, for maigesNorm class
    hierM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
          sLabelID="Sample", gLabelID="Name", doHeat=FALSE)

    ## If you want to show the heatmap do
    hierM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
          sLabelID="Sample", gLabelID="Name", doHeat=TRUE)

    ## If you want to show the hierarchical branch in both margins do
    hierM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
          sLabelID="Sample", gLabelID="Name", doHeat=TRUE, group="B")

    ## If you want to use euclidean distance only into rows (spots or genes)
    hierM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
          sLabelID="Sample", gLabelID="Name", doHeat=FALSE, group="R", distance="euclidean")

[Package maigesPack version 1.8.0 Index]