profileCGH consercion

Description

Convert a profileCGH object into a data.frame.

Usage

## S3 method for class 'profileCGH'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

Arguments

Details

The attributes profileValues and profileValuesNA are binded into a data.frame.

Value

A data.frame object

Note

People interested in tools dealing with array CGH analysis can visit our web-page http://bioinfo.curie.fr.

Author(s)

Philippe Hupé, glad@curie.fr

See Also

as.profileCGH

Examples

data(snijders)

### Creation of "profileCGH" object
profileCGH <- as.profileCGH(gm13330)



###########################################################
###
###  glad function as described in Hupé et al. (2004)
###
###########################################################


res <- glad(profileCGH, mediancenter=FALSE,
                smoothfunc="lawsglad", bandwidth=10, round=2,
                model="Gaussian", lkern="Exponential", qlambda=0.999,
                base=FALSE,
                lambdabreak=8, lambdacluster=8, lambdaclusterGen=40,
                type="tricubic", param=c(d=6),
                alpha=0.001, msize=5,
                method="centroid", nmax=8,
                verbose=FALSE)


res <- as.data.frame(res)

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(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.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/GLAD/as.data.frame.profileCGH.Rd_%03d_medium.png", width=480, height=480)
> ### Encoding: UTF-8
> 
> ### Name: as.data.frame.profileCGH
> ### Title: profileCGH consercion
> ### Aliases: as.data.frame.profileCGH
> ### Keywords: manip
> 
> ### ** Examples
> 
> 
> data(snijders)
> 
> ### Creation of "profileCGH" object
> profileCGH <- as.profileCGH(gm13330)
> 
> 
> 
> ###########################################################
> ###
> ###  glad function as described in Hupé et al. (2004)
> ###
> ###########################################################
> 
> 
> res <- glad(profileCGH, mediancenter=FALSE,
+                 smoothfunc="lawsglad", bandwidth=10, round=2,
+                 model="Gaussian", lkern="Exponential", qlambda=0.999,
+                 base=FALSE,
+                 lambdabreak=8, lambdacluster=8, lambdaclusterGen=40,
+                 type="tricubic", param=c(d=6),
+                 alpha=0.001, msize=5,
+                 method="centroid", nmax=8,
+                 verbose=FALSE)
[1] "Smoothing for each Chromosome"
[1] "Optimization of the Breakpoints"
[1] "Results Preparation"
> 
> 
> res <- as.data.frame(res)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>