rScudo

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see rScudo.

Signature-based Clustering for Diagnostic Purposes


Bioconductor version: 3.17

SCUDO (Signature-based Clustering for Diagnostic Purposes) is a rank-based method for the analysis of gene expression profiles for diagnostic and classification purposes. It is based on the identification of sample-specific gene signatures composed of the most up- and down-regulated genes for that sample. Starting from gene expression data, functions in this package identify sample-specific gene signatures and use them to build a graph of samples. In this graph samples are joined by edges if they have a similar expression profile, according to a pre-computed similarity matrix. The similarity between the expression profiles of two samples is computed using a method similar to GSEA. The graph of samples can then be used to perform community clustering or to perform supervised classification of samples in a testing set.

Author: Matteo Ciciani [aut, cre], Thomas Cantore [aut], Enrica Colasurdo [ctb], Mario Lauria [ctb]

Maintainer: Matteo Ciciani <matteo.ciciani at gmail.com>

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

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("rScudo")

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("rScudo")
Signature-based Clustering for Diagnostic Purposes HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews BiomedicalInformatics, Classification, Clustering, DifferentialExpression, FeatureExtraction, GeneExpression, GraphAndNetwork, Network, Proteomics, Software, SystemsBiology, Transcriptomics
Version 1.16.0
In Bioconductor since BioC 3.9 (R-3.6) (5 years)
License GPL-3
Depends R (>= 3.6)
Imports methods, stats, igraph, stringr, grDevices, Biobase, S4Vectors, SummarizedExperiment, BiocGenerics
System Requirements
URL https://github.com/Matteo-Ciciani/scudo
Bug Reports https://github.com/Matteo-Ciciani/scudo/issues
See More
Suggests testthat, BiocStyle, knitr, rmarkdown, ALL, RCy3, caret, e1071, parallel, doParallel
Linking To
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Build Report Build Report

Package Archives

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

Source Package rScudo_1.16.0.tar.gz
Windows Binary rScudo_1.16.0.zip
macOS Binary (x86_64) rScudo_1.16.0.tgz
macOS Binary (arm64) rScudo_1.16.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/rScudo
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/rScudo
Bioc Package Browser https://code.bioconductor.org/browse/rScudo/
Package Short Url https://bioconductor.org/packages/rScudo/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.17 Source Archive