kmeansMde {maigesPack} | R Documentation |
This is a function to do k-means clustering
analysis for objects of class maigesDEcluster
.
kmeansMde(data, group=c("C", "R")[1], distance="correlation", method="complete", sampleT=NULL, doHier=FALSE, sLabelID="SAMPLE", gLabelID="GeneName", idxTest=1, adjP="none", nDEgenes=0.05, ...)
data |
object of class maigesDEcluster . |
group |
character string giving the type of grouping: by rows 'R' or columns 'C' (default). |
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' |
sampleT |
list with 2 vectors. The first one specify the first letter of different sample types to be coloured by distinct colours, that are given in the second vector. If NULL (default) no colour is used. |
doHier |
logical indicating if you want to do the hierarchical branch in the opposite dimension of clustering. Defaults to FALSE. |
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 Kmeans function. |
This function implements the k-means clustering method for
objects resulted from differential analysis. The method uses
the function Kmeans
from package amap. 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 return invisibly a list
resulted from the function Kmeans
.
Gustavo H. Esteves <gesteves@vision.ime.usp.br>
Kmeans
from package
amap. mt.rawp2adjp
from package
multtest. somM
and hierM
for displaying SOM and
hierarchical 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") ## K-means cluster with 2 groups adjusting p-values by FDR, and showing all genes ## with p-value < 0.05 kmeansMde(gastro.ttest, sLabelID="Type", adjP="BH", nDEgenes=0.05, centers=2) ## K-means cluster with 3 groups adjusting p-values by FDR, and showing all genes ## with p-value < 0.05 kmeansMde(gastro.ttest, sLabelID="Type", adjP="BH", nDEgenes=0.05, centers=3) dev.off()