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TSGS  

Trait Specific Gene Selection using SVM and GA
View on CRAN: Click here


Download and install TSGS package within the R console
Install from CRAN:
install.packages("TSGS")

Install from Github:
library("remotes")
install_github("cran/TSGS")

Install by package version:
library("remotes")
install_version("TSGS", "1.0")



Attach the package and use:
library("TSGS")
Maintained by
Sudhir Srivastava
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-08
Latest Update: 2021-09-08
Description:
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.
How to cite:
Sudhir Srivastava (2021). TSGS: Trait Specific Gene Selection using SVM and GA. R package version 1.0, https://cran.r-project.org/web/packages/TSGS. Accessed 07 Jun. 2025.
Previous versions and publish date:
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Complete documentation for TSGS
Functions, R codes and Examples using the TSGS R package
Some associated functions: featureSelect . 
Some associated R codes: featureSelect.R .  Full TSGS package functions and examples
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