Matteo-Ciciani/scudo: 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
Maintainer
LicenseGPL-3
Version0.99.6
URL https://github.com/Matteo-Ciciani/scudo
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("Matteo-Ciciani/scudo")
Matteo-Ciciani/scudo documentation built on May 17, 2019, 11:06 a.m.