Packaged: 2016-02-24 23:10:44 UTC; DeenaGendoo

Description: A single-sample classifier that generates Medulloblastoma (MB) subtype predictions for single-samples of human Medulloblastoma (MB) patients and model systems, including cell lines and mouse-models. The MM2S algorithm uses a systems-based methodology that facilitates application of the algorithm on samples irrespective of their platform or source of origin. MM2S demonstrates > 96% accuracy for patients of well-characterized normal cerebellum, Wingless (WNT), or Sonic hedgehog (SHH) subtypes, and the less-characterized Group4 (86%) and Group3 (78.2%). MM2S also enables classification of MB cell lines and mouse models into their human counterparts.This package contains function for implementing the classifier onto human data and mouse data, as well as graphical rendering of the results as PCA (Principal Component Analysis) plots and heatmaps. Deena Gendoo and Benjamin Haibe-Kains (2016) <doi:10.1186/s13029-016-0053-y>.

Title: Gene Expression Datasets for the 'MM2S' Package
Description: Gene Expression datasets for the 'MM2S' package. Contains normalized expression data for Human Medulloblastoma ('GSE37418') as well as Mouse Medulloblastoma models ('GSE36594').
Packaged: 2015-06-12 16:16:00 UTC; DeenaGendoo

Packaged: 2015-06-16 20:45:01 UTC; DeenaGendoo

Description: Gene Expression datasets for the 'MM2S' package. Contains normalized expression data for Human Medulloblastoma ('GSE37418') as well as Mouse Medulloblastoma models ('GSE36594'). Deena Gendoo et al. (2015) <doi:10.1016/j.ygeno.2015.05.002>.

Title: Inference of Linear Mixed Models Through MM Algorithm
Author: Fabien Laporte, Tristan Mary-Huard
Description: The main function MMEst() performs (Restricted) Maximum Likelihood in a variance component mixed models using a Min-Max (MM) algorithm (Hunter, D. R., & Lange, K. (2004) <doi:10.1198/0003130042836>).
Imports: Rcpp (>= 0.12.13), Matrix, parallel, stats

Imports: Rcpp (>= 0.12.13), Matrix, parallel, stats, MASS

Imports: Rcpp (>= 0.12.13), Matrix, parallel, stats, MASS, utils