Plots the profile of a SeqCNAInfo-class object.

Description

The plotted elements depend on the processing applied on the SeqCNAInfo-class object.

Usage

plotCNProfile(rco, folder = NULL)

Arguments

Value

Nothing is returned from this function. Check the folder folder for a file called seqnorm_out.jpg.

Author(s)

David Mosen-Ansorena

Examples

data(seqsumm_HCC1143)
rco = readSeqsumm(tumour.data=seqsumm_HCC1143)
rco = applyFilters(rco, 0, 1, 0, 2, FALSE, plots=FALSE)
rco = runSeqnorm(rco, plots=FALSE)
rco = runGLAD(rco)
rco = applyThresholds(rco, seq(-0.9,4,by=0.9), 1)

plotCNProfile(rco)

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(seqCNA)
Loading required package: GLAD

######################################################################################

Have fun with GLAD

For smoothing it is possible to use either
the AWS algorithm (Polzehl and Spokoiny, 2002,
or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics,  2008,

If you use the package with AWS, please cite:
Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,

If you use the package with HaarSeg, please cite:
Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,

For fast computation it is recommanded to use
the daglad function with smoothfunc=haarseg

######################################################################################

New options are available in daglad: see help for details.

Loading required package: doSNOW
Loading required package: foreach
Loading required package: iterators
Loading required package: snow
Loading required package: adehabitatLT
Loading required package: sp
Loading required package: ade4
Loading required package: adehabitatMA
Loading required package: CircStats
Loading required package: MASS
Loading required package: boot
Loading required package: seqCNA.annot
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/seqCNA/plotCNProfile.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotCNProfile
> ### Title: Plots the profile of a 'SeqCNAInfo-class' object.
> ### Aliases: plotCNProfile
> ### Keywords: Output
> 
> ### ** Examples
> 
> data(seqsumm_HCC1143)
> rco = readSeqsumm(tumour.data=seqsumm_HCC1143)
Note: chromosome lengths will be estimated from sample.
Reading summarized data...
> rco = applyFilters(rco, 0, 1, 0, 2, FALSE, plots=FALSE)
Note: GC content will be estimated from sample.
Applying filters...
  Windows without reads or info: 164
  Total filtered windows:        212
  Remaining windows:             5102
> rco = runSeqnorm(rco, plots=FALSE)
Creating segments...
  Segments total: 173
  Segments passing QC: 7
Fitting regression models...
> rco = runGLAD(rco)
Running segmentation...
> rco = applyThresholds(rco, seq(-0.9,4,by=0.9), 1)
> 
> plotCNProfile(rco)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>