rScudo

DOI: 10.18129/B9.bioc.rScudo    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see rScudo.

Signature-based Clustering for Diagnostic Purposes

Bioconductor version: 3.15

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>

Installation

To install this package, start R (version "4.2") 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")

 

HTML	R Script	Signature-based Clustering for Diagnostic Purposes
PDF		Reference Manual
Text		NEWS

Details

biocViews	BiomedicalInformatics, Classification, Clustering, DifferentialExpression, FeatureExtraction, GeneExpression, GraphAndNetwork, Network, Proteomics, Software, SystemsBiology, Transcriptomics
Version	1.12.0
In Bioconductor since	BioC 3.9 (R-3.6) (3.5 years)
License	GPL-3
Depends	R (>= 3.6)
Imports	methods, stats, igraph, stringr, grDevices, Biobase, S4Vectors, SummarizedExperiment, BiocGenerics
LinkingTo
Suggests	testthat, BiocStyle, knitr, rmarkdown, ALL, RCy3, caret, e1071, parallel, doParallel
SystemRequirements
Enhances
URL	https://github.com/Matteo-Ciciani/scudo
BugReports	https://github.com/Matteo-Ciciani/scudo/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	rScudo_1.12.0.tar.gz
Windows Binary	rScudo_1.12.0.zip (64-bit only)
macOS Binary (x86_64)	rScudo_1.12.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/rScudo
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/rScudo
Package Short Url	https://bioconductor.org/packages/rScudo/
Package Downloads Report	Download Stats