| hierM {maigesPack} | R Documentation |
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.
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, ...)
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. |
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.
This function display the heatmaps and don't return any object or value.
Gustavo H. Esteves <gesteves@vision.ime.usp.br>
somM and kmeansM for displaying SOM and
k-means clusters, respectively.
## 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")