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pbcmc : Permutation-Based Confidence for Molecular Classification

Package: pbcmc
Type: Package
Title: Permutation-Based Confidence for Molecular Classification
Version: 1.0.0
Date: 2016-04-04
Author: Cristobal Fresno, German A. Gonzalez, Andrea S. Llera and Elmer
A. Fernandez
Maintainer: Cristobal Fresno <cristobalfresno@gmail.com>
Description: The pbcmc package characterizes uncertainty assessment on
gene expression classifiers, a. k. a. molecular signatures,
based on a permutation test. In order to achieve this goal,
synthetic simulated subjects are obtained by permutations of
gene labels. Then, each synthetic subject is tested against the
corresponding subtype classifier to build the null
distribution. Thus, classification confidence measurement can
be provided for each subject, to assist physician therapy
choice. At present, it is only available for PAM50
implementation in genefu package but it can easily be extend to
other molecular signatures.
URL: http://www.bdmg.com.ar/
License: GPL (>=2)
Depends: R (>= 3.3.0), genefu
Imports: Biobase, BiocGenerics, BiocParallel (>= 1.3.13), parallel,
reshape2, grid, utils, cowplot, methods, limma, ggplot2,
gridExtra, grDevices, stats
Suggests: breastCancerUPP, breastCancerNKI, breastCancerVDX,
breastCancerTRANSBIG, breastCancerMAINZ, breastCancerUNT
biocViews: Classification, GeneExpression, Microarray,
MultipleComparison, QualityControl, Normalization, Clustering,
mRNAMicroarray, OneChannel, TwoChannel, RNASeq, KEGG,
DifferentialExpression
Collate: 'pbcmcPackage.R' 'MolecularPermutationClassifierClass.R'
'MolecularPermutationClassifierConstructor.R'
'MolecularPermutationClassifierGenerics.R'
'MolecularPermutationClassifierGetseters.R'
'MolecularPermutationClassifierShow.R' 'PAM50Class.R'
'PAM50Classify.R' 'PAM50Constructor.R' 'PAM50Filtrate.R'
'PAM50Permutate.R' 'PAM50Report.R' 'PAM50Subtype.R'
'pbcmcData.R'
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-05-04 06:57:17 UTC; biocbuild

● Data Source: BioConductor
● BiocViews: Classification, Clustering, DifferentialExpression, GeneExpression, KEGG, Microarray, MultipleComparison, Normalization, OneChannel, QualityControl, RNASeq, TwoChannel, mRNAMicroarray
3 images, 13 functions, 1 datasets
● Reverse Depends: 0