This is the released version of rScudo; for the devel version, see rScudo.
Signature-based Clustering for Diagnostic PurposesBioconductor version: Release (3.21)
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, entercitation("rScudo")): Installation
To install this package, start R (version "4.5") 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.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("rScudo")Follow Installation instructions to use this package in your R session.
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