Package: GLAD 2.69.0

Philippe Hupe

GLAD: Gain and Loss Analysis of DNA

Analysis of array CGH data : detection of breakpoints in genomic profiles and assignment of a status (gain, normal or loss) to each chromosomal regions identified.

Authors:Philippe Hupe

GLAD_2.69.0.tar.gz
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GLAD.pdf |GLAD.html✨
GLAD/json (API)

# Install 'GLAD' in R:
install.packages('GLAD', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • gsl– GNU Scientific Library (GSL)
  • c++– GNU Standard C++ Library v3
Datasets:
  • P20 - Public CGH data of Veltman
  • P9 - Public CGH data of Veltman
  • array1 - Bladder cancer CGH data
  • array2 - Bladder cancer CGH data
  • array3 - Bladder cancer CGH data
  • cytoband - Cytogenetic banding
  • gm00143 - Public CGH data of Snijders
  • gm01524 - Public CGH data of Snijders
  • gm01535 - Public CGH data of Snijders
  • gm01750 - Public CGH data of Snijders
  • gm02948 - Public CGH data of Snijders
  • gm03134 - Public CGH data of Snijders
  • gm03563 - Public CGH data of Snijders
  • gm03576 - Public CGH data of Snijders
  • gm04435 - Public CGH data of Snijders
  • gm05296 - Public CGH data of Snijders
  • gm07081 - Public CGH data of Snijders
  • gm07408 - Public CGH data of Snijders
  • gm10315 - Public CGH data of Snijders
  • gm13031 - Public CGH data of Snijders
  • gm13330 - Public CGH data of Snijders

On BioConductor:GLAD-2.69.0(bioc 3.20)GLAD-2.68.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

66 exports 5.84 score 3 dependencies 3 dependents 81 mentions

Last updated 2 months agofrom:55fd28b238

Exports:affectationGNLaffectationGNL.profileCGHarrayPersparrayPersp.arrayCGHarrayPersp.defaultarrayPlotarrayPlot.arrayCGHarrayPlot.defaultas.data.frame.profileCGHas.profileCGHas.profileCGH.data.frameBkpInfoBkpInfo.profileCGHCheckDataCheckData.profileCGHchrBreakpointschrBreakpoints.profileCGHChrNumericclustergladclusterglad.hclustColorBardagladdaglad.profileCGHDelRegionTooSmalldetectOutliersdetectOutliers.profileChrdogenomestepFDRThresfilterBkpfilterBkp.profileCGHfilterBkpStepfilterBkpStep.profileCGHfindClusterfindCluster.profileChrgladglad.profileCGHHaarSegHaarSegGLADHaarSegGLADCPPhclustgladkernelpenlawsgladloopRemoveloopRemove.profileChrMoveBkpMoveBkp.profileCGHMoveBkpStepMoveBkpStep.profileCGHmyPaletteOptimBkpFindClusterOutliersGNLOutliersGNL.profileCGHplotCytoBandplotCytoBand.defaultplotProfileplotProfile.profileCGHprepare.output.dagladRecomputeGNLremoveBreakpointsremoveBreakpoints.profileChrremoveLevelremoveLevel.profileChrSegmentByPeaksselectindextestBkpToMovetestBkpToMove.profileCGH

Dependencies:awsawsMethodsgsl

GLAD

Rendered fromGLAD.Rnwusingutils::Sweaveon Jul 03 2024.

Last update: 2020-04-15
Started: 2013-11-01

Readme and manuals

Help Manual

Help pageTopics
Bladder cancer CGH dataarray1 array2 array3
Object of Class arrayCGHarrayCGH
Perspective image of microarray spots statisticarrayPersp arrayPersp.arrayCGH arrayPersp.default
Spatial image of microarray spots statisticarrayPlot arrayPlot.arrayCGH arrayPlot.default
profileCGH consercionas.data.frame.profileCGH
Create an object of class profileCGHas.profileCGH as.profileCGH.data.frame
Convert chromosome into numeric valuesChrNumeric
Calibration bar for color imagesColorBar
Cytogenetic bandingcytoband
Analysis of array CGH datadaglad daglad.profileCGH
Analysis of array CGH dataglad glad.profileCGH
Hierarchical Clusteringhclustglad
Kernelpen functionkernelpen
Microarray color palettemyPalette
Plot genomic profile and cytogenetic bandingplotProfile plotProfile.profileCGH
Objects of Class profileCGH and profileChrprofileCGH profileChr
Public CGH data of Snijdersgm00143 gm01524 gm01535 gm01750 gm02948 gm03134 gm03563 gm03576 gm04435 gm05296 gm07081 gm07408 gm10315 gm13031 gm13330
Public CGH data of VeltmanP20 P9