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MBMethPred
View on CRAN: Click
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Download and install MBMethPred package within the R console
Install from CRAN:
install.packages("MBMethPred")
Install from Github:
library("remotes")
install_github("cran/MBMethPred")
Install by package version:
library("remotes")
install_version("MBMethPred", "0.1.4.2")
Attach the package and use:
library("MBMethPred")
Maintained by
Edris Sharif Rahmani
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-13
Latest Update: 2023-09-18
Description:
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. for more details.
How to cite:
Edris Sharif Rahmani (2022). MBMethPred: Medulloblastoma Subgroups Prediction. R package version 0.1.4.2, https://cran.r-project.org/web/packages/MBMethPred
Previous versions and publish date:
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Other R packages that MBMethPred depends,
imports, suggests or enhances
Functions, R codes and Examples using
the MBMethPred R package
Some associated functions: BoxPlot . ConfusionMatrix . Data1 . Data2 . Data3 . KNearestNeighborModel . LinearDiscriminantAnalysisModel . ModelMetrics . NaiveBayesModel . NeuralNetworkModel . NewDataPredictionResult . RLabels . RandomForestModel . ReadMethylFile . ReadSNFData . SimilarityNetworkFusion . SupportVectorMachineModel . TSNEPlot . XGBoostModel .
Some associated R codes: globals.R . Full MBMethPred package functions and examples
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