Medulloblastoma Subgroups Prediction R package MBMethPred version 0.1.4.4 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. Software 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 Edris Sharif Rahmani <rahmani.biotech@gmail.com> Comprehensive R Archive Network (CRAN) Edris Sharif Rahmani [aut, ctb, cre] (ORCID: <https://orcid.org/0000-0002-7899-1663>), Ankita Sunil Lawarde [aut, ctb] (ORCID: <https://orcid.org/0000-0001-7572-4431>), Vijayachitra Modhukur [aut, ctb] (ORCID: <https://orcid.org/0000-0002-7123-9903>) GPL 2025-12-04 application/tgz https://CRAN.R-project.org/package=MBMethPred doi:10.32614/CRAN.package.MBMethPred