Matteo-Ciciani/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.

Getting started

Package details

Bioconductor views BiomedicalInformatics Classification Clustering DifferentialExpression FeatureExtraction GeneExpression GraphAndNetwork Network Proteomics SystemsBiology Transcriptomics
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
Matteo-Ciciani/rScudo documentation built on May 26, 2020, 1:21 p.m.