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maigesPack : Functions to handle cDNA microarray data, including several methods of data analysis

Package: maigesPack
Version: 1.36.0
Title: Functions to handle cDNA microarray data, including several
methods of data analysis
Author: Gustavo H. Esteves <gesteves@gmail.com>, with contributions
from Roberto Hirata Jr <hirata@ime.usp.br>, E. Jordao Neves
<neves@ime.usp.br>, Elier B. Cristo <elier@ime.usp.br>, Ana C.
Simoes <anakqui@ime.usp.br> and Lucas Fahham
<fahham@linux.ime.usp.br>
Maintainer: Gustavo H. Esteves <gesteves@gmail.com>
Depends: R (>= 2.10), convert, graph, limma, marray, methods
Suggests: amap, annotate, class, e1071, MASS, multtest, OLIN, R2HTML,
rgl, som
Description: This package uses functions of various other packages
together with other functions in a coordinated way to handle
and analyse cDNA microarray data
License: GPL (>= 2)
LazyLoad: yes
Collate: AllClasses.R AllGenerics.R print-methods.R summary-methods.R
show-methods.R dim-methods.R indexing-methods.R
coerce-methods.R plot-methods.R image-methods.R
boxplot-methods.R calcA-methods.R calcW-methods.R
getLabels-methods.R activeMod.R activeModScoreHTML.R
activeNet.R activeNetScoreHTML.R addGeneGrps.R addPaths.R
bootstrapCor.R bootstrapMI.R bootstrapT.R classifyKNN.R
classifyKNNsc.R classifyLDA.R classifyLDAsc.R classifySVM.R
classifySVMsc.R colors.R compCorr.R contrastsFitM.R
createMaigesRaw.R createTDMS.R deGenes2by2BootT.R
deGenes2by2Ttest.R deGenes2by2Wilcox.R deGenesANOVA.R
designANOVA.R heatmapsM.R hierMde.R hierM.R kmeansMde.R
kmeansM.R loadData.R MI.R normLoc.R normOLIN.R normRepLoess.R
normScaleLimma.R normScaleMarray.R plotGenePair.R relNet2TGF.R
relNetworkB.R relNetworkM.R robustCorr.R selSpots.R somMde.R
somM.R summarizeReplicates.R tableClass.R tablesDE.R
URL: http://www.maiges.org/en/software/
biocViews: Microarray, TwoChannel, Preprocessing, ThirdPartyClient,
DifferentialExpression, Clustering, Classification,
GraphAndNetwork
NeedsCompilation: yes
Packaged: 2016-05-04 03:03:43 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Classification, Clustering, DifferentialExpression, GraphAndNetwork, Microarray, Preprocessing, ThirdPartyClient, TwoChannel
47 images, 70 functions, 1 datasets
● Reverse Depends: 0

convert : Convert Microarray Data Objects

Package: convert
Version: 1.48.0
Title: Convert Microarray Data Objects
Author: Gordon Smyth <smyth@wehi.edu.au>,
James Wettenhall <wettenhall@wehi.edu.au>,
Yee Hwa (Jean Yang) <jean@biostat.ucsf.edu>,
Martin Morgan <mtmorgan@fhcrc.org>Martin Morgan
Maintainer: Yee Hwa (Jean) Yang <jean@biostat.ucsf.edu>
Depends: R (>= 2.6.0), Biobase (>= 1.15.33), limma (>= 1.7.0), marray,
utils, methods
Description: Define coerce methods for microarray data objects.
License: LGPL
URL: http://bioinf.wehi.edu.au/limma/convert.html
biocViews: Infrastructure, Microarray, TwoChannel
NeedsCompilation: no
Packaged: 2016-05-04 02:41:28 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Infrastructure, Microarray, TwoChannel
● 0 images, 1 functions, 0 datasets
Reverse Depends: 2

dyebias : The GASSCO method for correcting for slide-dependent gene-specific dye bias

Package: dyebias
Title: The GASSCO method for correcting for slide-dependent
gene-specific dye bias
Version: 1.32.0
Date: 2 March 2016
Author: Philip Lijnzaad and Thanasis Margaritis
Description: Many two-colour hybridizations suffer from a dye bias that is
both gene-specific and slide-specific. The former depends on the content of
the nucleotide used for labeling; the latter depends on the labeling
percentage. The slide-dependency was hitherto not recognized, and made
addressing the artefact impossible. Given a reasonable number of
dye-swapped pairs of hybridizations, or of same vs. same hybridizations,
both the gene- and slide-biases can be estimated and corrected using the
GASSCO method (Margaritis et al., Mol. Sys. Biol. 5:266 (2009),
doi:10.1038/msb.2009.21)
Maintainer: Philip Lijnzaad <plijnzaad@gmail.com>
License: GPL-3
Depends: R (>= 1.4.1), marray, Biobase
Suggests: limma, convert, GEOquery, dyebiasexamples, methods
URL: http://www.holstegelab.nl/publications/margaritis_lijnzaad
biocViews: Microarray, TwoChannel, QualityControl, Preprocessing
NeedsCompilation: no
Packaged: 2016-05-05 02:02:45 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Microarray, Preprocessing, QualityControl, TwoChannel
3 images, 9 functions, 0 datasets
● Reverse Depends: 0

dyebiasexamples : Example data for the dyebias package, which implements the GASSCO method.

Package: dyebiasexamples
Version: 1.12.0
Date: 2 March 2016
Title: Example data for the dyebias package, which implements the
GASSCO method.
Author: Philip Lijnzaad and Thanasis Margaritis
Description: Data for the dyebias package, consisting of 4 self-self
hybrizations of self-spotted yeast slides, as well as data
from Array Express accession E-MTAB-32
Maintainer: Philip Lijnzaad <plijnzaad@gmail.com>
License: GPL-3
Depends: R (>= 1.4.1), marray, GEOquery
Suggests: dyebias, convert, Biobase
URL: http://www.holstegelab.nl/publications/margaritis_lijnzaad
biocViews: ExperimentData, SAGEData, CGHData, MicroarrayData,
TwoChannelData, ArrayExpress
NeedsCompilation: no
Packaged: 2016-05-07 20:16:40 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: ArrayExpress, CGHData, ExperimentData, MicroarrayData, SAGEData, TwoChannelData
● 0 images, 2 functions, 1 datasets
● Reverse Depends: 0

stepNorm : Stepwise normalization functions for cDNA microarrays

Package: stepNorm
Version: 1.44.0
Date: 2008-10-08
Title: Stepwise normalization functions for cDNA microarrays
Author: Yuanyuan Xiao <yxiao@itsa.ucsf.edu>, Yee Hwa (Jean) Yang
<jean@biostat.ucsf.edu>
Depends: R (>= 1.8.0), marray, methods
Imports: marray, MASS, methods, stats
Maintainer: Yuanyuan Xiao <yxiao@itsa.ucsf.edu>
Description: Stepwise normalization functions for cDNA microarray
data.
License: LGPL
URL: http://www.biostat.ucsf.edu/jean/
biocViews: Microarray, TwoChannel, Preprocessing
NeedsCompilation: no
Packaged: 2016-05-04 02:43:12 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Microarray, Preprocessing, TwoChannel
● 0 images, 11 functions, 0 datasets
● Reverse Depends: 0

OLIN : Optimized local intensity-dependent normalisation of two-color microarrays

Package: OLIN
Version: 1.50.0
Date: 2016-02-19
Title: Optimized local intensity-dependent normalisation of two-color
microarrays
Author: Matthias Futschik <mfutschik@ualg.pt>
Maintainer: Matthias Futschik <mfutschik@ualg.pt>
Depends: R (>= 2.10), methods, locfit, marray
Imports: graphics, grDevices, limma, marray, methods, stats
Suggests: convert
Description: Functions for normalisation of two-color microarrays by optimised local regression and for detection of artefacts in microarray data
biocViews: Microarray, TwoChannel, QualityControl, Preprocessing,
Visualization
License: GPL-2
URL: http://olin.sysbiolab.eu
NeedsCompilation: no
Packaged: 2016-05-04 02:42:29 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Microarray, Preprocessing, QualityControl, TwoChannel, Visualization
30 images, 34 functions, 3 datasets
Reverse Depends: 1

RBM : RBM: a R package for microarray and RNA-Seq data analysis

biocViews: Microarray, DifferentialExpression
Package: RBM
Version: 1.4.0
Date: 2014-10-02
Title: RBM: a R package for microarray and RNA-Seq data analysis
Author: Dongmei Li and Chin-Yuan Liang
Maintainer: Dongmei Li <Dongmei_Li@urmc.rochester.edu>
Depends: R (>= 3.2.0), limma, marray
Description: Use A Resampling-Based Empirical Bayes Approach to Assess
Differential Expression in Two-Color Microarrays and RNA-Seq
data sets.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2016-05-04 06:11:54 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: DifferentialExpression, Microarray
● 0 images, 3 functions, 1 datasets
● Reverse Depends: 0

TurboNorm : A fast scatterplot smoother suitable for microarray normalization

Package: TurboNorm
Type: Package
Title: A fast scatterplot smoother suitable for microarray
normalization
Version: 1.20.0
Date: 2014-18-08
Author: Maarten van Iterson and Chantal van Leeuwen
Maintainer: Maarten van Iterson <mviterson@gmail.com>
Description: A fast scatterplot smoother based on B-splines with second-order difference penalty. Functions for microarray normalization of single-colour data i.e. Affymetrix/Illumina and two-colour data supplied as marray MarrayRaw-objects or limma RGList-objects are available.
License: LGPL
LazyLoad: yes
Depends: R (>= 2.12.0), convert, limma (>= 1.7.0), marray
Imports: stats, grDevices, affy, lattice
Suggests: BiocStyle, affydata
biocViews: Microarray, OneChannel, TwoChannel, Preprocessing,
DNAMethylation, CpGIsland, MethylationArray, Normalization
URL: http://www.humgen.nl/MicroarrayAnalysisGroup.html
NeedsCompilation: yes
Packaged: 2016-05-04 03:53:07 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: CpGIsland, DNAMethylation, MethylationArray, Microarray, Normalization, OneChannel, Preprocessing, TwoChannel
5 images, 5 functions, 1 datasets
● Reverse Depends: 0

MineICA : Analysis of an ICA decomposition obtained on genomics data

Package: MineICA
Type: Package
Title: Analysis of an ICA decomposition obtained on genomics data
Version: 1.12.0
Date: 2012-03-16
Author: Anne Biton
Maintainer: Anne Biton <anne.biton@gmail.com>
Description: The goal of MineICA is to perform Independent Component
Analysis (ICA) on multiple transcriptome datasets, integrating
additional data (e.g molecular, clinical and pathological).
This Integrative ICA helps the biological interpretation of the
components by studying their association with variables (e.g
sample annotations) and gene sets, and enables the comparison
of components from different datasets using correlation-based
graph.
License: GPL-2
LazyLoad: yes
Depends: R (>= 2.10), methods, BiocGenerics (>= 0.13.8), Biobase, plyr,
ggplot2, scales, foreach, xtable, biomaRt, gtools, GOstats,
cluster, marray, mclust, RColorBrewer, colorspace, igraph,
Rgraphviz, graph, annotate, Hmisc, fastICA, JADE
Imports: AnnotationDbi, lumi, fpc, lumiHumanAll.db
Suggests: biomaRt, GOstats, cluster, hgu133a.db, mclust, igraph,
breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP,
breastCancerVDX
Enhances: doMC
Collate: 'AllClasses.R' 'AllGeneric.R' 'methods-IcaSet.R'
'methods-MineICAParams.R' 'compareAnalysis.R'
'functions_comp2annot.R' 'functions_comp2annottests.R'
'functions_enrich.R' 'functions.R' 'heatmap.plus.R'
'heatmapsOnSel.R' 'runAn.R' 'compareGenes.R'
biocViews: Visualization, MultipleComparison
NeedsCompilation: no
Packaged: 2016-05-05 03:47:04 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: MultipleComparison, Visualization
7 images, 66 functions, 7 datasets
● Reverse Depends: 0

nnNorm : Spatial and intensity based normalization of cDNA microarray data based on robust neural nets

Package: nnNorm
Version: 2.36.0
Date: 2010-04-13
Title: Spatial and intensity based normalization of cDNA microarray
data based on robust neural nets
Author: Adi Laurentiu Tarca <atarca@med.wayne.edu>
Depends: R (>= 2.2.0), marray
Imports: graphics, grDevices, marray, methods, nnet, stats
Maintainer: Adi Laurentiu Tarca <atarca@med.wayne.edu>
Description: This package allows to detect and correct for spatial and intensity biases with two-channel microarray data.
The normalization method implemented in this package is based on robust neural networks fitting.
biocViews: Microarray, TwoChannel, Preprocessing
License: LGPL
URL: http://bioinformaticsprb.med.wayne.edu/tarca/
NeedsCompilation: no
Packaged: 2016-05-04 02:42:48 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Microarray, Preprocessing, TwoChannel
3 images, 3 functions, 0 datasets
● Reverse Depends: 0