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SVMDO

This is the development version of SVMDO; for the stable release version, see SVMDO.

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


Bioconductor version: Development (3.19)

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 wilk’s 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.

Author: Mustafa Erhan Ozer [aut, cre] , Pemra Ozbek Sarica [aut], Kazim Yalcin Arga [aut]

Maintainer: Mustafa Erhan Ozer <erhanozer19 at marun.edu.tr>

Citation (from within R, enter citation("SVMDO")):

Installation

To install this package, start R (version "4.4") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("SVMDO")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("SVMDO")
SVMDO-Tutorial HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Classification, DifferentialExpression, GUI, GeneSetEnrichment, RNASeq, Software, Survival, Transcriptomics
Version 1.3.2
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License GPL-3
Depends R (>= 4.3), 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), 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
System Requirements
URL
Bug Reports https://github.com/robogeno/SVMDO/issues
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Suggests BiocStyle, knitr, rmarkdown, testthat (>= 3.1.6)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package SVMDO_1.3.2.tar.gz
Windows Binary SVMDO_1.3.2.zip
macOS Binary (x86_64) SVMDO_1.3.2.tgz
macOS Binary (arm64) SVMDO_1.3.2.tgz
Source Repository git clone https://git.bioconductor.org/packages/SVMDO
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/SVMDO
Bioc Package Browser https://code.bioconductor.org/browse/SVMDO/
Package Short Url https://bioconductor.org/packages/SVMDO/
Package Downloads Report Download Stats