Package: IGST 0.1.0

IGST: Informative Gene Selection Tool

Mining informative genes with certain biological meanings are 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 selects the informative genes related to a specific trait using gene expression dataset. These trait specific genes are considered as informative genes. This package returns the informative gene set from the high dimensional gene expression data using a combination of methods SVM and MRMR (for feature selection) with bootstrapping procedure.

Authors:Nitesh Kumar Sharma, Dwijesh Chandra Mishra, Neeraj Budhlakoti and Md. Samir Farooqi

IGST_0.1.0.tar.gz
IGST_0.1.0.zip(r-4.5)IGST_0.1.0.zip(r-4.4)IGST_0.1.0.zip(r-4.3)
IGST_0.1.0.tgz(r-4.4-any)IGST_0.1.0.tgz(r-4.3-any)
IGST_0.1.0.tar.gz(r-4.5-noble)IGST_0.1.0.tar.gz(r-4.4-noble)
IGST_0.1.0.tgz(r-4.4-emscripten)IGST_0.1.0.tgz(r-4.3-emscripten)
IGST.pdf |IGST.html
IGST/json (API)

# Install 'IGST' in R:
install.packages('IGST', repos = c('https://nitzzzzzzz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • rice_cold - A gene expression dataset of rice under cold stress

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 6 scripts 102 downloads 4 exports 5 dependencies

Last updated 5 years agofrom:50dc0a6309. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winOKOct 30 2024
R-4.5-linuxOKOct 30 2024
R-4.4-winOKOct 30 2024
R-4.4-macOKOct 30 2024
R-4.3-winOKOct 30 2024
R-4.3-macOKOct 30 2024

Exports:IGST.bootmrmrsvm.pval.cutoffIGST.bootmrmrsvm.weight.cutoffIGST.pval.bootmrmrsvmIGST.weight.bootmrmrsvm

Dependencies:BootMRMRclasse1071MASSproxy