pbcmc: Permutation-Based Confidence for Molecular Classification

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.

Package details

AuthorCristobal Fresno, German A. Gonzalez, Andrea S. Llera and Elmer A. Fernandez
Bioconductor views Classification Clustering DifferentialExpression GeneExpression KEGG Microarray MultipleComparison Normalization OneChannel QualityControl RNASeq TwoChannel mRNAMicroarray
MaintainerCristobal Fresno <cristobalfresno@gmail.com>
LicenseGPL (>=2)
URL http://www.bdmg.com.ar/
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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pbcmc documentation built on Nov. 1, 2018, 2:09 a.m.