plot read enrichment profiles at a specific peak for all specified samples.

Description

plot read enrichment profiles at a specific peak for all specified samples.

Usage

plotPeak(DBA, Peak.id, Sample.ids = NULL, NormMethod = 'DESeq',
        plot.input = TRUE, fieldname = "PeakRawHists",
        save2file = FALSE, fn.pics)

Arguments

Author(s)

Gabriele Schweikert

See Also

getPeakProfiles, getNormFactors, plotHistDists

Examples

# load DBA objects with peak profiles 
data(Cfp1Profiles)
plotPeak(Cfp1Profiles, Peak.id=20, NormMethod=NULL)

# plot normalized profiles of WT.AB2 and Resc.AB2 samples,  don't plot
# the input:

Cfp1Norm <- getNormFactors(Cfp1Profiles)
Sample.ids <- c("WT.AB2", "Resc.AB2")
plotPeak(Cfp1Norm, Peak.id=20, Sample.ids=Sample.ids,
      NormMethod='DESeq', plot.input = FALSE)

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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> library(MMDiff)
Loading required package: GenomicRanges
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: 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: DiffBind
Loading required package: SummarizedExperiment
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")'.


Loading required package: GMD
Loading required package: Rsamtools
Loading required package: Biostrings
Loading required package: XVector
Warning message:
Package 'MMDiff' is deprecated and will be removed from Bioconductor
  version 3.4 
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MMDiff/plotPeak.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotPeak
> ### Title: plot read enrichment profiles at a specific peak for all
> ###   specified samples.
> ### Aliases: plotPeak
> 
> ### ** Examples
> 
> 
> # load DBA objects with peak profiles 
> data(Cfp1Profiles)
> plotPeak(Cfp1Profiles, Peak.id=20, NormMethod=NULL)
No normalization factors applied
> 
> # plot normalized profiles of WT.AB2 and Resc.AB2 samples,  don't plot
> # the input:
> 
> Cfp1Norm <- getNormFactors(Cfp1Profiles)
Computing Scaling factor according to DESeq normalization method
Using all Samples: nSamples = 3
Samples:
[1] "WT.AB2"   "Null.AB2" "Resc.AB2"
Using unfiltered Peaks
nPeaks = 1000 (of 1000)
appending NormTotalCounts
Determined Factors:
$`WT.AB2,Null.AB2,Resc.AB2`
     WT_2    Null_2    Resc_2 
0.9439729 0.8899213 1.1986945 

> Sample.ids <- c("WT.AB2", "Resc.AB2")
> plotPeak(Cfp1Norm, Peak.id=20, Sample.ids=Sample.ids,
+       NormMethod='DESeq', plot.input = FALSE)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>