Description Usage Arguments Details Value Author(s) See Also Examples
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
.
1 2 3 4 |
data |
object of class |
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 |
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
|
geneGrp |
numerical or character specifying the gene group to be
clustered. This is given by the columns of the slot |
path |
numerical or character specifying the gene network to be
clustered. This is given by the items of the slot |
... |
additional parameters for |
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ## 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")
|
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