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Analysis of big data from aCGH experiments using parallel computing and ff objects

Bioconductor version: 3.0

Analysis and plotting of array CGH data. Allows usage of Circular Binary Segementation, wavelet-based smoothing (both as in Liu et al., and HaarSeg as in Ben-Yaacov and Eldar), HMM, BioHMM, GLAD, CGHseg. Most computations are parallelized (either via forking or with clusters, including MPI and sockets clusters) and use ff for storing data.

Author: Ramon Diaz-Uriarte <rdiaz02 at> and Oscar M. Rueda < at>. Wavelet-based aCGH smoothing code from Li Hsu <lih at> and Douglas Grove <dgrove at>. Imagemap code from Barry Rowlingson <B.Rowlingson at>. HaarSeg code from Erez Ben-Yaacov; downloaded from <>.

Maintainer: Ramon Diaz-Uriarte <rdiaz02 at>

Citation (from within R, enter citation("ADaCGH2")):


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PDF R Script ADaCGH2 Overview
PDF ADaCGH2-long-examples.pdf
PDF benchmarks.pdf
PDF   Reference Manual
Text   NEWS


biocViews CopyNumberVariants, Microarray, Software
Version 2.6.0
In Bioconductor since BioC 2.7 (R-2.12)
License GPL (>= 3)
Depends R (>= 2.15.0), parallel, ff
Imports bit, ffbase, DNAcopy, tilingArray, GLAD, waveslim, cluster, aCGH, snapCGH
Suggests CGHregions, Cairo, limma
Enhances Rmpi
Depends On Me
Imports Me
Suggests Me
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