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EpiSemble

0.1.1

Ensemble Based Machine Learning Approach for Predicting Methylation States

0packages depend
2.4Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Dipro SinhaFirst published 2022-08-222 releasesCRAN page ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 6.1 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
19
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-05-02
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
  • ERROR2026-04-25
    11 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
0%
Documented parameters
100%
Return-value docs
100%
References docs
100%

Downloads

2.4K
CRAN downloads in the past year
Rank #15,514 · ~7/day · ~199/mo
Daily download trend is not available in this view yet.
19830 days
67590 days
2.4K1 year
Compare downloads with other packages →
Also on103 r2u

Dependencies

Declared dependencies
17 external dependencies (excludes base and recommended)
Depends (0)
none
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (5)
Maintainer (1)
Author, Maintainer
Authors (5)
Author, Maintainer
Author
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 0.1.1Latest
    2023-06-04 · current release · diff ↗
  • unarchivedReturned to CRAN
    2023-06-04
  • R
    R 4.3.0 released · 2023-04-21
  • archivedRemoved from CRAN
    2023-04-07
    issues were not corrected in time
  • 0.1.0
    2022-08-22
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2022-08-22
Total releases
2 / 4 yrs
License
GPL-3 OSI
Download size
1.0 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("EpiSemble")
Sinha, D., Archak, S., Dasmandal, T., Mishra, D. C., & Yeasin, M. (2023). EpiSemble: Ensemble Based Machine Learning Approach for Predicting Methylation States (Version 0.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.EpiSemble

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for EpiSemble version 0.1.1 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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