Bladder cancer data from 3 arrays CGH (Comparative Genomic
Hybridyzation). Arrays dimension are 4 blocs per column, 4 blocs per
row, 21 columns per bloc and 22 rows by blocs.
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(GLAD)
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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
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New options are available in daglad: see help for details.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/GLAD/bladder.Rd_%03d_medium.png", width=480, height=480)
> ### Name: array
> ### Title: Bladder cancer CGH data
> ### Aliases: array1 array2 array3
> ### Keywords: datasets
>
> ### ** Examples
>
> data(arrayCGH)
> data <- array1 #array1 to array3
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>
>
>
>
> dev.off()
null device
1
>