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)
The Medullo-Model To Subtypes (MM2S) classifier stratifies single MB gene expression profiles without reference samples or replicates. Our pathway-centric approach facilitates subtype predictions of patient samples, and model systems including cell lines and mouse models.
The manuscript link is:
http://www.sciencedirect.com/science/article/pii/S0888754315000774
The MM2S and MM2Sdata packages are available on CRAN:
** To install the MM2S and the MM2Sdata packages, from within an R terminal, please type:
install.packages("MM2S", repos="http://cran.r-project.org")
library(MM2S)
install.packages("MM2Sdata", repos="http://cran.r-project.org")
library(MM2Sdata)
** Load the libraries in R:
library(MM2S)
library(MM2Sdata)
** To install dependencies of the package, please run the following in R:
install.packages("BiocManager", repos="http://cran.r-project.org")
rr <- BiocManager::install(pkgs=c("GSVA", "kknn", "lattice", "pheatmap"), dependencies=TRUE, type="source", destdir=".")