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.

AuthorCristobal Fresno, German A. Gonzalez, Andrea S. Llera and Elmer A. Fernandez
Date of publicationNone
MaintainerCristobal Fresno <cristobalfresno@gmail.com>
LicenseGPL (>=2)
Version1.2.2
http://www.bdmg.com.ar/

View on Bioconductor

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.