Description: A single-sample classifier that generates Medulloblastoma (MB) subtype predictions for single-samples of human 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 plots and heatmaps.
|Depends:||GSVA (≥ 1.13.1), kknn (≥ 1.2-5), parallel, lattice, pheatmap, R (≥ 2.10)|
|Imports:||datasets, grDevices, graphics, stats, utils|
|Author:||Deena M.A. Gendoo, Benjamin Haibe-Kains|
|Maintainer:||Deena M.A. Gendoo <deena.gendoo at utoronto.ca>|
|CRAN checks:||MM2S results|
MM2S An Introduction (HowTo)
MM2S An Introduction (HowTo) from Raw Data
|Windows binaries:||r-devel: MM2S_1.0.5.zip, r-release: MM2S_1.0.5.zip, r-oldrel: MM2S_1.0.5.zip|
|OS X Mavericks binaries:||r-release: MM2S_1.0.5.tgz, r-oldrel: not available|
|Old sources:||MM2S archive|
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