- recipe bioconductor-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 bioconductor-rscudo¶
- depends bioconductor-biobase:
- depends bioconductor-biocgenerics:
- depends bioconductor-s4vectors:
- depends bioconductor-summarizedexperiment:
- depends r-base:
- depends r-igraph:
- depends r-stringr:
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install bioconductor-rscudo and update with:: mamba update bioconductor-rscudo
To create a new environment, run:
mamba create --name myenvname bioconductor-rscudo
myenvnamebeing a reasonable name for the environment (see e.g. the mamba docs for details and further options).
Alternatively, use the docker container:
docker pull quay.io/biocontainers/bioconductor-rscudo:<tag> (see `bioconductor-rscudo/tags`_ for valid values for ``<tag>``)