Plotting ChIP profiles of one or more clusters

Description

plotProfiles plots the ChIP profiles of one or more clusters. Additionally on can display the distribution of e.g. gene expression in the clusters.

Usage

plotProfiles(profiles, mfcol=NULL, mfrow=NULL, ylab="intensity", xlab="position", histograms=NULL, cluster, profileplot=T, meanprofile=T, ...)

Arguments

Author(s)

Benedikt Zacher zacher@lmb.uni-muenchen.de

See Also

density, profileplot

Examples

## 
sampls = 100
probes = 63
clus = matrix(rnorm(probes*sampls,sd=1),ncol=probes)
clus= rbind( t(t(clus)+sin(1:probes/10))+1:nrow(clus)/sampls , t(t(clus)+sin(pi/2+1:probes/10))+1:nrow(clus)/sampls )
clustering = kmeans(clus,3)$cluster
names(clustering) <- 1:length(clustering)


profiles <- apply(clus, 1, function(x) {list(upstream=x[1:20], region=x[21:43], downstream=x[44:63])})
names(profiles) <- 1:length(clustering)
profiles <- list(profile=profiles, upstream=20, downstream=20, borderNames=c("start", "stop"))

plotProfiles(profiles, cluster=clustering, ylim=c(-1,2.5), type="l", lwd=2)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(Starr)
Loading required package: Ringo
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: RColorBrewer
Loading required package: limma

Attaching package: 'limma'

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

    plotMA

Loading required package: Matrix
Loading required package: grid
Loading required package: lattice
Loading required package: affy

Attaching package: 'affy'

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

    probes

Loading required package: affxparser

Attaching package: 'Starr'

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

    plotDensity

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

    plotMA

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

    plotMA

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Starr/plotProfiles.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotProfiles
> ### Title: Plotting ChIP profiles of one or more clusters
> ### Aliases: plotProfiles
> ### Keywords: hplot
> 
> ### ** Examples
> 
> ## 
> sampls = 100
> probes = 63
> clus = matrix(rnorm(probes*sampls,sd=1),ncol=probes)
> clus= rbind( t(t(clus)+sin(1:probes/10))+1:nrow(clus)/sampls , t(t(clus)+sin(pi/2+1:probes/10))+1:nrow(clus)/sampls )
> clustering = kmeans(clus,3)$cluster
> names(clustering) <- 1:length(clustering)
> 
> 
> profiles <- apply(clus, 1, function(x) {list(upstream=x[1:20], region=x[21:43], downstream=x[44:63])})
> names(profiles) <- 1:length(clustering)
> profiles <- list(profile=profiles, upstream=20, downstream=20, borderNames=c("start", "stop"))
> 
> plotProfiles(profiles, cluster=clustering, ylim=c(-1,2.5), type="l", lwd=2)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>