rScudo: Signature-based Clustering for Diagnostic Purposes

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.

Package details

AuthorMatteo Ciciani [aut, cre], Thomas Cantore [aut], Enrica Colasurdo [ctb], Mario Lauria [ctb]
Bioconductor views BiomedicalInformatics Classification Clustering DifferentialExpression FeatureExtraction GeneExpression GraphAndNetwork Network Proteomics SystemsBiology Transcriptomics
MaintainerMatteo Ciciani <>
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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rScudo documentation built on Nov. 8, 2020, 5:07 p.m.