Skip to content

EpiSemble

Ensemble Based Machine Learning Approach for Predicting Methylation States

v0.1.1 · Jun 4, 2023 · GPL-3

Description

DNA methylation (6mA) is a major epigenetic process by which alteration in gene expression took place without changing the DNA sequence. Predicting these sites in-vitro is laborious, time consuming as well as costly. This 'EpiSemble' package is an in-silico pipeline for predicting DNA sequences containing the 6mA sites. It uses an ensemble-based machine learning approach by combining Support Vector Machine (SVM), Random Forest (RF) and Gradient Boosting approach to predict the sequences with 6mA sites in it. This package has been developed by using the concept of Chen et al. (2019) <doi:10.1093/bioinformatics/btz015>.

Downloads

252

Last 30 days

17544th

636

Last 90 days

2.4K

Last year

Trend: +18.3% (30d vs prior 30d)

CRAN Check Status

14 OK
Show all 14 flavors
Flavor Status
r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies devtools tidyverse seqinr Biostrings splitstackshape entropy party stringr tibble doParallel e1071 caret randomForest gbm foreach +2 more dependencies EpiSemble

Version History

new 0.1.1 Mar 10, 2026
updated 0.1.1 ← 0.1.0 diff Jun 3, 2023
new 0.1.0 Aug 21, 2022