ReadSNFData

A function to read user-provided file feeding into the SNF function (from the SNFtools package).

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.

Edris Sharif Rahmani

MBMethPred

Medulloblastoma Subgroups Prediction

Ankita Sunil Lawarde

Vijayachitra Modhukur

ReadSNFData function

<dl><dt>File</dt>
<dd>A data frame with tsv or csv file extension. The first column of the data frame is the CpG methylation probe that starts with cg characters and is followed by a number (e.g., cg100091). Other columns are samples with methylation beta values. All columns in the data frame should have a name.</dd></dl>

Arguments

Input file for similarity network fusion (SNF) — ReadSNFData

<dl>

<dt>File</dt>
<dd>A data frame with tsv or csv file extension. The first column of the data frame is the CpG methylation probe that starts with cg characters and is followed by a number (e.g., cg100091). Other columns are samples with methylation beta values. All columns in the data frame should have a name.</dd>

</dl>

ReadSNFData: Input file for similarity network fusion (SNF)

Description

Usage

Value

Arguments

Examples