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Last data update: 2014.03.03

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Results 1 - 4 of 4 found.
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seqCNA : Copy number analysis of high-throughput sequencing cancer data

Package: seqCNA
Type: Package
Title: Copy number analysis of high-throughput sequencing cancer data
Version: 1.18.0
Date: 2015-01-09
Author: David Mosen-Ansorena
Maintainer: David Mosen-Ansorena <dmosen.gn@cicbiogune.es>
Import: GLAD, doSNOW, adehabitatLT, seqCNA.annot
Depends: R (>= 3.0), GLAD (>= 2.14), doSNOW (>= 1.0.5), adehabitatLT
(>= 0.3.4), seqCNA.annot (>= 0.99), methods
Description: Copy number analysis of high-throughput sequencing cancer
data with fast summarization, extensive filtering and improved
normalization
License: GPL-3
SystemRequirements: samtools
biocViews: CopyNumberVariation, Genetics, Sequencing
NeedsCompilation: yes
Packaged: 2016-05-04 05:01:01 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, Genetics, Sequencing
● 1 images, 10 functions, 1 datasets
● Reverse Depends: 0

ITALICS : ITALICS

Package: ITALICS
Version: 2.32.0
Date: 2008-05-14
Title: ITALICS
Depends: R (>= 2.0.0), GLAD, ITALICSData, oligo, affxparser,
pd.mapping50k.xba240
Imports: affxparser, DBI, GLAD, oligo, oligoClasses, stats
Suggests: pd.mapping50k.hind240, pd.mapping250k.sty, pd.mapping250k.nsp
Author: Guillem Rigaill, Philippe Hupe
Maintainer: Guillem Rigaill <italics@curie.fr>
Description: A Method to normalize of Affymetrix GeneChip Human Mapping
100K and 500K set
License: GPL-2
URL: http://bioinfo.curie.fr
biocViews: Microarray, CopyNumberVariation
NeedsCompilation: no
Packaged: 2016-05-04 03:09:38 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, Microarray
● 0 images, 14 functions, 0 datasets
● Reverse Depends: 0

ADaCGH2 : Analysis of big data from aCGH experiments using parallel computing and ff objects

Package: ADaCGH2
Version: 2.12.0
Date: 2016-04-29
Title: Analysis of big data from aCGH experiments using parallel
computing and ff objects
Author: Ramon Diaz-Uriarte <rdiaz02@gmail.com> and Oscar M. Rueda <rueda.om@gmail.com>. Wavelet-based aCGH smoothing code from Li Hsu <lih@fhcrc.org> and Douglas Grove <dgrove@fhcrc.org>. Imagemap code from Barry Rowlingson <B.Rowlingson@lancaster.ac.uk>. HaarSeg code from Erez Ben-Yaacov; downloaded from <http://www.ee.technion.ac.il/people/YoninaEldar/Info/software/HaarSeg.htm>.
Maintainer: Ramon Diaz-Uriarte <rdiaz02@gmail.com>
Depends: R (>= 3.2.0), parallel, ff, GLAD
Imports: bit, ffbase, DNAcopy, tilingArray, waveslim, cluster, aCGH,
snapCGH
Suggests: CGHregions, Cairo, limma
Enhances: Rmpi
Description: 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.
biocViews: Microarray, CopyNumberVariants
LazyLoad: Yes
License: GPL (>= 3)
URL: https://github.com/rdiaz02/adacgh2
NeedsCompilation: yes
Packaged: 2016-05-04 03:48:32 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariants, Microarray
● 0 images, 5 functions, 1 datasets
● Reverse Depends: 0

MANOR : CGH Micro-Array NORmalization

Package: MANOR
Version: 1.44.0
Date: 2015-05-27
Title: CGH Micro-Array NORmalization
Author: Pierre Neuvial <pierre.neuvial@genopole.cnrs.fr>, Philippe Hupe
<philippe.hupe@curie.fr>
Maintainer: Pierre Neuvial <pierre.neuvial@genopole.cnrs.fr>
Depends: R (>= 2.10), GLAD
Imports: GLAD, graphics, grDevices, stats, utils
Description: Importation, normalization, visualization, and quality
control functions to correct identified sources of variability
in array-CGH experiments.
License: GPL-2
URL: http://bioinfo.curie.fr/projects/manor/index.html
biocViews: Microarray, TwoChannel, DataImport, QualityControl,
Preprocessing, CopyNumberVariation
NeedsCompilation: yes
Packaged: 2016-05-04 02:47:53 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CopyNumberVariation, DataImport, Microarray, Preprocessing, QualityControl, TwoChannel
● 10 images, 16 functions, 3 datasets
● Reverse Depends: 0