Clustering of Most Variable Genes

Description

The function pamCluster selects the ngenes most variable genes and performs their clustering using the partitioning around medoids method pam.

Usage

pamCluster(ngenes, x, k = 2)

Arguments

Value

Integer vector specifying the clustering.

Author(s)

Wolfgang Huber

See Also

pam

Examples

data("x")
y = x[, x$Embryonic.day=="E3.5"]

## perform the clustering 
pc = pamCluster(50, y, k=3)

## display clustering vs. sample lineage
plot(as.factor(pData(y)$lineage), pc, yaxt="n", xlab="lineage", ylab="cluster")

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)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(Hiiragi2013)
Loading required package: affy
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Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

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    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

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Loading required package: mouse4302.db
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> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Hiiragi2013/pamCluster.Rd_%03d_medium.png", width=480, height=480)
> ### Name: pamCluster
> ### Title: Clustering of Most Variable Genes
> ### Aliases: pamCluster
> 
> ### ** Examples
> 
> data("x")
> y = x[, x$Embryonic.day=="E3.5"]
> 
> ## perform the clustering 
> pc = pamCluster(50, y, k=3)
> 
> ## display clustering vs. sample lineage
> plot(as.factor(pData(y)$lineage), pc, yaxt="n", xlab="lineage", ylab="cluster")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>