rScudo
This is the released version of rScudo; for the devel version, see rScudo.
Signature-based Clustering for Diagnostic Purposes
Bioconductor version: Release (3.20)
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("rScudo")):
Installation
To install this package, start R (version "4.4") 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 | ||
| NEWS | Text |
Details
| biocViews | BiomedicalInformatics, Classification, Clustering, DifferentialExpression, FeatureExtraction, GeneExpression, GraphAndNetwork, Network, Proteomics, Software, SystemsBiology, Transcriptomics |
| Version | 1.22.0 |
| In Bioconductor since | BioC 3.9 (R-3.6) (5.5 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 | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | rScudo_1.22.0.tar.gz |
| Windows Binary (x86_64) | rScudo_1.22.0.zip (64-bit only) |
| macOS Binary (x86_64) | rScudo_1.22.0.tgz |
| macOS Binary (arm64) | rScudo_1.22.0.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 |