MBMethPred: Medulloblastoma Subgroups Prediction

Utilizing a combination of machine learning models (Random Forest, Naive Bayes, K-Nearest Neighbor, Support Vector Machines, Extreme Gradient Boosting, and Linear Discriminant Analysis) and a deep Artificial Neural Network model, 'MBMethPred' can predict medulloblastoma subgroups, including wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4 from DNA methylation beta values. See Sharif Rahmani E, Lawarde A, Lingasamy P, Moreno SV, Salumets A and Modhukur V (2023), MBMethPred: a computational framework for the accurate classification of childhood medulloblastoma subgroups using data integration and AI-based approaches. Front. Genet. 14:1233657. <doi:10.3389/fgene.2023.1233657> for more details.

Depends: R (≥ 3.5.0)
Imports: stringr, ggplot2, parallel, caTools, caret, keras, MASS, Rtsne, SNFtool, class, dplyr, e1071, pROC, randomForest, readr, reshape2, reticulate, rgl, tensorflow, xgboost
Suggests: knitr, rmarkdown, testthat, utils, stats, scales
Published: 2023-09-18
Author: Edris Sharif Rahmani ORCID iD [aut, ctb, cre], Ankita Sunil Lawarde ORCID iD [aut, ctb], Vijayachitra Modhukur ORCID iD [aut, ctb]
Maintainer: Edris Sharif Rahmani <rahmani.biotech at gmail.com>
BugReports: https://github.com/sharifrahmanie/MBMethPred/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/sharifrahmanie/MBMethPred
NeedsCompilation: no
CRAN checks: MBMethPred results


Reference manual: MBMethPred.pdf
Vignettes: MBMethPred introduction


Package source: MBMethPred_0.1.4.2.tar.gz
Windows binaries: r-devel: MBMethPred_0.1.4.2.zip, r-release: MBMethPred_0.1.4.2.zip, r-oldrel: MBMethPred_0.1.4.2.zip
macOS binaries: r-release (arm64): MBMethPred_0.1.4.2.tgz, r-oldrel (arm64): MBMethPred_0.1.4.2.tgz, r-release (x86_64): MBMethPred_0.1.4.2.tgz, r-oldrel (x86_64): MBMethPred_0.1.4.2.tgz
Old sources: MBMethPred archive


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