CRAN/E | EpiSemble

EpiSemble

Ensemble Based Machine Learning Approach for Predicting Methylation States

Installation

About

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.

Key Metrics

Version 0.1.0
Published 2022-08-22 606 days ago
Needs compilation? no
License GPL-3
CRAN checks EpiSemble results

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Maintainer

Maintainer

Dipro Sinha

diprosinha@gmail.com

Authors

Dipro Sinha

aut / cre

Sunil Archak

aut

Dwijesh Chandra Mishra

aut

Tanwy Dasmandal

aut

Md Yeasin

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Imports

stats
devtools
tidyverse
seqinr
Biostrings
splitstackshape
entropy
party
stringr
tibble
doParallel
parallel
e1071
caret
randomForest
gbm
foreach
ftrCOOL
iterators