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bioc
ASURAT:Functional annotation-driven unsupervised clustering for single-cell data
ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).
Maintained by Keita Iida. Last updated 5 months ago.
geneexpressionsinglecellsequencingclusteringgenesignalingcpp
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