methylClass: an R package to construct DNA methylation-based classification models.

ensemble feature selection methylation multi-omics pan-cancer support vector machine

Journal

Briefings in bioinformatics
ISSN: 1477-4054
Titre abrégé: Brief Bioinform
Pays: England
ID NLM: 100912837

Informations de publication

Date de publication:
22 Nov 2023
Historique:
received: 03 08 2023
revised: 02 12 2023
accepted: 05 12 2023
medline: 11 1 2024
pubmed: 11 1 2024
entrez: 11 1 2024
Statut: ppublish

Résumé

DNA methylation profiling is a useful tool to increase the accuracy of a cancer diagnosis. However, a comprehensive R package specially for it is lacking. Hence, we developed the R package methylClass for methylation-based classification. Within it, we provide the eSVM (ensemble-based support vector machine) model to achieve much higher accuracy in methylation data classification than the popular random forest model and overcome the time-consuming problem of the traditional SVM. In addition, some novel feature selection methods are included in the package to improve the classification. Furthermore, because methylation data can be converted to other omics, such as copy number variation data, we also provide functions for multi-omics studies. The testing of this package on four datasets shows the accurate performance of our package, especially eSVM, which can be used in both methylation and multi-omics models and outperforms other methods in both cases. methylClass is available at: https://github.com/yuabrahamliu/methylClass.

Identifiants

pubmed: 38205965
pii: 7513599
doi: 10.1093/bib/bbad485
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press.

Auteurs

Yu Liu (Y)

Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892, USA.

Classifications MeSH