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SVMDO

Identification of Tumor-Discriminating mRNA Signatures via Support Vector Machines Supported by Disease Ontology

Bioconductor version: 3.23 · Package version: 1.12.0

It is an easy-to-use GUI using disease information for detecting tumor/normal sample discriminating gene sets from differentially expressed genes. Our approach is based on an iterative algorithm filtering genes with disease ontology enrichment analysis and wilk and wilks lambda criterion connected to SVM classification model construction. Along with gene set extraction, SVMDO also provides individual prognostic marker detection. The algorithm is designed for FPKM and RPKM normalized RNA-Seq transcriptome datasets.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SVMDO")

Details

MaintainerMustafa Erhan Ozer <erhanozer19@marun.edu.tr>
AuthorMustafa Erhan Ozer [aut, cre] (ORCID: <https://orcid.org/0000-0002-1572-8008>), Pemra Ozbek Sarica [aut], Kazim Yalcin Arga [aut]
LicenseGPL-3
Bug Reportshttps://github.com/robogeno/SVMDO/issues
Downloads rank192
Source branchRELEASE_3_23
biocViewsClassification, DifferentialExpression, GUI, GeneSetEnrichment, RNASeq, Software, Survival, Transcriptomics

Documentation

Download

Dependencies

Depends: R (>= 4.4), shiny (>= 1.7.4)

Imports: shinyFiles (>= 0.9.3), shinytitle (>= 0.1.0), golem (>= 0.3.5), nortest (>= 1.0-4), e1071 (>= 1.7-12), BSDA (>= 1.2.1), data.table (>= 1.14.6), sjmisc (>= 2.8.9), klaR (>= 1.7-1), caTools (>= 1.18.2), caret (>= 6.0-93), survival (>= 3.4-0), DT (>= 0.33.0), DOSE (>= 3.24.2), AnnotationDbi (>= 1.60.0), org.Hs.eg.db (>= 3.16.0), dplyr (>= 1.0.10), SummarizedExperiment (>= 1.28.0), grDevices, graphics, stats, utils

Suggests: BiocStyle, knitr, rmarkdown, testthat (>= 3.1.6)