Function to do SOM cluster analysis

Description

This is a function to do SOM (Self Organising Maps) clustering analysis for objects of classes maiges, maigesRaw and maigesANOVA. Use the function somMde for objects of class maigesDEcluster.

Usage

somM(data, group=c("C", "R")[1], distance="correlation",
     method="complete", sampleT=NULL, doHier=FALSE, sLabelID="SAMPLE",
     gLabelID="GeneName", rmGenes=NULL, rmSamples=NULL, rmBad=TRUE,
     geneGrp=NULL, path=NULL, ...)

Arguments

Details

This function implements the SOM clustering method for objects of microarray data defined in this package. The method uses the function som from package som.

Value

This function display the heatmaps and return invisibly an object of class som resulted from the function som.

Author(s)

Gustavo H. Esteves <gesteves@vision.ime.usp.br>

See Also

som from package som. kmeansM and hierM for displaying k-means and hierarchical clusters, respectively.

Examples

## Loading the dataset
data(gastro)

## Doing a SOM cluster with 2 groups using all genes, for maigesRaw class
somM(gastro.raw, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
     sLabelID="Sample", gLabelID="Name", xdim=2, ydim=1, topol="rect")

## Doing a SOM cluster with 3 groups using all genes, for maigesNorm class
somM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
     sLabelID="Sample", gLabelID="Name", xdim=3, ydim=1, topol="rect")

## Another example with 4 groups
somM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
     sLabelID="Sample", gLabelID="Name", xdim=2, ydim=2, topol="rect")

## If you want to use euclidean distance to group genes (or spots), with
## 3 groups
somM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
     sLabelID="Sample", gLabelID="Name", group="R",
     distance="euclidean", xdim=3, ydim=1, topol="rect")

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/somM.Rd_%03d_medium.png", width=480, height=480)
> ### Name: somM
> ### Title: Function to do SOM cluster analysis
> ### Aliases: somM
> ### Keywords: hplot
> 
> ### ** Examples
> 
> ## Loading the dataset
> data(gastro)
> 
> ## Doing a SOM cluster with 2 groups using all genes, for maigesRaw class
> somM(gastro.raw, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
+      sLabelID="Sample", gLabelID="Name", xdim=2, ydim=1, topol="rect")
Warning message:
In as.matrix(log2(tmp1$R)) : NaNs produced
> 
> ## Doing a SOM cluster with 3 groups using all genes, for maigesNorm class
> somM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
+      sLabelID="Sample", gLabelID="Name", xdim=3, ydim=1, topol="rect")
> 
> ## Another example with 4 groups
> somM(gastro.norm, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
+      sLabelID="Sample", gLabelID="Name", xdim=2, ydim=2, topol="rect")
> 
> ## If you want to use euclidean distance to group genes (or spots), with
> ## 3 groups
> somM(gastro.summ, rmGenes=c("BLANK","DAP","LYS","PHE", "Q_GENE","THR","TRP"),
+      sLabelID="Sample", gLabelID="Name", group="R",
+      distance="euclidean", xdim=3, ydim=1, topol="rect")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>