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")