DOI: 10.18129/B9.bioc.rScudo  

This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see rScudo.

Signature-based Clustering for Diagnostic Purposes

Bioconductor version: 3.16

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>

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biocViews BiomedicalInformatics, Classification, Clustering, DifferentialExpression, FeatureExtraction, GeneExpression, GraphAndNetwork, Network, Proteomics, Software, SystemsBiology, Transcriptomics
Version 1.14.0
In Bioconductor since BioC 3.9 (R-3.6) (4 years)
License GPL-3
Depends R (>= 3.6)
Imports methods, stats, igraph, stringr, grDevices, Biobase, S4Vectors, SummarizedExperiment, BiocGenerics
Suggests testthat, BiocStyle, knitr, rmarkdown, ALL, RCy3, caret, e1071, parallel, doParallel
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