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.
Details
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.
Value
This function display the heatmaps and don't return any object or value.
somM and kmeansM for displaying SOM and
k-means clusters, respectively.
Examples
## 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)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(maigesPack)
Loading required package: convert
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: limma
Attaching package: 'limma'
The following object is masked from 'package:BiocGenerics':
plotMA
Loading required package: marray
Loading required package: graph
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/maigesPack/hierMde.Rd_%03d_medium.png", width=480, height=480)
> ### Name: hierMde
> ### Title: Function to do hierarchical cluster analysis
> ### Aliases: hierMde
> ### Keywords: hplot
>
> ### ** Examples
>
> ## 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)
>
>
>
>
>
> dev.off()
null device
1
>