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EpiSemble

0.1.1Package record

Ensemble Based Machine Learning Approach for Predicting Methylation States

0packages depend
2.6Kdownloads / year
–test coverage
13/13flavors OK

Overview

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.

Install

Health

CRAN checks
13OK
Slowest check: 5.1 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK13 OK2026-05-02
Show 2 earlier changesHide 2 earlier changes
  • ERROR11 OK, 1 ERROR2026-04-25
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.1
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
2
Examples that run
0%2 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
100%

Downloads

2.6K
CRAN downloads in the past year
Rank #16,501 · ~7/day · ~219/mo
Daily download trend is not available in this view yet.
26130 days
76690 days
2.6K1 year
Compare downloads with other packages →
Also on72 r2u

Dependencies

Declared dependencies
17 external dependencies (excludes base and recommended)

Installing EpiSemble adds 194 packages (90 with compiled code, 128 MB of source tarballs). Heaviest: stringi 11 MB, TH.data 8.2 MB, ggplot2 6.0 MB. 1 more not on CRAN is not measured.

Depends (0)
none
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (5)
Author, Maintainer since 0.1.0 (2022)
Author
Releases (2)

Pick two releases to compare their code metrics.

  • 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
  • unarchivedReturned to CRAN
    2023-06-04
  • 0.1.1Latest
    record
    2023-06-04 · current release · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • archivedRemoved from CRAN
    2023-04-07
    issues were not corrected in time
  • 0.1.0
    record
    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

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 package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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