Package: cn.farms
Title: cn.FARMS - factor analysis for copy number estimation
Version: 1.14.0
Date: 2014-05-19
Type: Package
License: LGPL (>= 2.0)
Author: Andreas Mitterecker, Djork-Arne Clevert
Maintainer: Andreas Mitterecker <mitterecker@bioinf.jku.at>
Description: This package implements the cn.FARMS algorithm for copy
        number variation (CNV) analysis. cn.FARMS allows to analyze the
        most common Affymetrix (250K-SNP6.0) array types, supports
        high-performance computing using snow and ff.
URL: http://www.bioinf.jku.at/software/cnfarms/cnfarms.html
Depends: R (>= 3.0), Biobase, methods, ff, oligoClasses, snow
Imports: DBI, affxparser, oligo, DNAcopy, preprocessCore, lattice
Suggests: pd.mapping250k.sty, pd.mapping250k.nsp, pd.genomewidesnp.5,
        pd.genomewidesnp.6
Collate: 'callSummarize.R' 'combineData.R' 'correctPkgname.R'
        'cnFarms.R' 'createAnnotation.R' 'createMatrix.R'
        'determineBaselineArray.R' 'distributionDistance.R'
        'dnaCopySf.R' 'doCnFarms.R' 'fragLengthCorr.R' 'normAdd.R'
        'normalizeAverage.R' 'normalizeCels.R' 'normalizeNpData.R'
        'normalizeQuantiles.R' 'normalizeSor.R' 'plotDendrogram.R'
        'plotDensity.R' 'plotEvalIc.R' 'plotSmoothScatter.R'
        'plotsRegions.R' 'plotViolines.R' 'sparseFarmsC.R'
        'summarizationMl.R' 'summarizationSl.R'
        'summarizeFarmsGaussian.R' 'summarizeFarmsLaplaceExact.R'
        'summarizeFarmsLaplaceVar.R' 'summarizeFarmsMethods.R'
        'summarizeStatistics.R' 'windowFunctions.R' 'windowMethods.R'
        'normalizeProbeSequence.R' 'snowfallExt.R'
        'summarizeFarmsLaplaceExact2.R' 'summarizeFarmsLaplaceExact3.R'
        'normalizeNone.R' 'utils-lds.R' 'zzz.R' 'sFclusterFunctions.R'
        'sFinit.R' 'sFsnowfall-internal.R' 'sFsnowWrappers.R'
        'sFsocketRequest.R' 'vanillaIce.R'
biocViews: Microarray, CopyNumberVariation
Roxygen: list(wrap = FALSE)
Packaged: 2014-10-14 03:24:35 UTC; biocbuild
Built: R 3.1.1; i386-w64-mingw32; 2014-10-14 07:22:57 UTC; windows
Archs: i386, x64
