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Trait Specific Gene Selection using SVM and GA

0packages depend
2.8Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

Obtaining relevant set of trait specific genes from gene expression data is important for clinical diagnosis of disease and discovery of disease mechanisms in plants and animals. This process involves identification of relevant genes and removal of redundant genes as much as possible from a whole gene set. This package returns the trait specific gene set from the high dimensional RNA-seq count data by applying combination of two conventional machine learning algorithms, support vector machine (SVM) and genetic algorithm (GA). GA is used to control and optimize the subset of genes sent to the SVM for classification and evaluation. Genetic algorithm uses repeated learning steps and cross validation over number of possible solution and selects the best. The algorithm selects the set of genes based on a fitness function that is obtained via support vector machines. Using SVM as the classifier performance and the genetic algorithm for feature selection, a set of trait specific gene set is obtained.

Install

Health

CRAN checks
13OK
Slowest check: 5.2 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-09-08
  • ERROR12 OK, 1 ERROR2026-09-07
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
Show 6 earlier changesHide 6 earlier changes
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK13 OK2026-05-02
  • ERROR11 OK, 1 ERROR2026-04-25
  • OK14 OK2026-04-17
  • WARNING13 OK, 1 WARNING2026-04-16
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.1
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
1
Examples that run
100%1 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

2.8K
CRAN downloads in the past year
Rank #9,362 · ~8/day · ~237/mo
Daily download trend is not available in this view yet.
44030 days
1K90 days
2.8K1 year
Compare downloads with other packages →
Also on78 r2u

Repository

0Stars
0Forks
1Open issues
0Open PRs
1Releases
7Commits
2Commit identities
7 commits · Last activity 2021-08-27 · The default branch showed an older version (1.0) than CRAN on 2026-10-18
Responsiveness
not measured

Releases over time

2021-08-11 · 12026-07-07 · 1
PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/sudhirsrivastava/tsgs on 2026-10-18.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)

Installing TSGS adds 66 packages (36 with compiled code, 49 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 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.

Datasets

People & History

People (4)
Maintainer since 1.0 (2021), Author
Releases (2)

Pick two releases to compare their code metrics.

  • 1.0.1Latest
    record
    2026-07-07 · current release · diff ↗
  • 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
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • 1.0
    record
    2021-09-08
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2021-09-08
Total releases
2 / 5 yrs
License
GPL-2 | GPL-3 OSI
Download size
43 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("TSGS")
Srivastava, S., Chaturvedi, K. K., Farooqi, M. S., & Mishra, D. C. (2026). TSGS: Trait Specific Gene Selection using SVM and GA (Version 1.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.TSGS

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 TSGS version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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