csClusterPlot

Description

Replaces the default plotting behavior of the old csCluster. Takes as an argument the output of csCluster and plots expression profiles of features facet by cluster.

Usage

csClusterPlot(clustering, pseudocount=1.0,logMode=FALSE,drawSummary=TRUE,sumFun=mean_cl_boot)

Arguments

Details

This replaces the default plotting behavior of the old csCluster() method. This was necessary so as to preserve the cluster information obtained by csCluster in a stable format. The output of csClusterPlot is a ggplot2 object of expressionProfiles faceted by cluster ID.

Value

A ggplot2 object of expressionProfiles faceted by cluster ID.

Note

None.

Author(s)

Loyal A. Goff

References

None.

Examples

	data(sampleData)
	myClustering<-csCluster(sampleGeneSet,k=4)
	csClusterPlot(myClustering)

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(cummeRbund)
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

Loading required package: RSQLite
Loading required package: DBI
Loading required package: ggplot2
Loading required package: reshape2
Loading required package: fastcluster

Attaching package: 'fastcluster'

The following object is masked from 'package:stats':

    hclust

Loading required package: rtracklayer
Loading required package: GenomicRanges
Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

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

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Gviz
Loading required package: grid

Attaching package: 'cummeRbund'

The following object is masked from 'package:GenomicRanges':

    promoters

The following object is masked from 'package:IRanges':

    promoters

The following object is masked from 'package:BiocGenerics':

    conditions

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/cummeRbund/csClusterPlot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: csClusterPlot
> ### Title: csClusterPlot
> ### Aliases: csClusterPlot
> 
> ### ** Examples
> 
> 	data(sampleData)
> 	myClustering<-csCluster(sampleGeneSet,k=4)
Loading required package: cluster
Using tracking_id, sample_name as id variables
> 	csClusterPlot(myClustering)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>