hierMde {maigesPack} | R Documentation |
This is a function to do hierarchical clustering
analysis for objects of classe maigesDEcluster
.
hierMde(data, group=c("C", "R", "B")[1], distance="correlation", method="complete", doHeat=TRUE, sLabelID="SAMPLE", gLabelID="GeneName", idxTest=1, adjP="BH", nDEgenes=0.05, ...)
data |
object of class 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. |
idxTest |
numerical index of the test to be used to sort the
genes when clustering objects of class maigesDEcluster . |
adjP |
string specifying the method of p-value adjustment. May be 'none', 'Bonferroni', 'Holm', 'Hochberg', 'SidakSS', 'SidakSD', 'BH', 'BY'. |
nDEgenes |
number of DE genes to be selected. If a real number
in (0,1) all genes with p.value <= nDEgenes will be
used. If an integer, the nDEgenes genes with smaller
p-values will be used. |
... |
additional parameters for heatmap function. |
This function implements the hierarchical clustering method for
objects resulted from differential expression analysis. The default
function for hierarchical clustering is the
hclust
. For the adjustment of p-values in the
selection of genes differentially expressed, we use the function
mt.rawp2adjp
from package multtest.
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 bootstrap from t statistic test fot 'Type' sample label, k=1000 ## specifies one thousand bootstraps gastro.ttest = deGenes2by2Ttest(gastro.summ, sLabelID="Type") ## Hierarchical cluster adjusting p-values by FDR, and showing all genes ## with p-value < 0.05 hierMde(gastro.ttest, sLabelID="Type", adjP="BH", nDEgenes=0.05)