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R Codebase for BISCUIT: Infinite Mixture Model to cluster and impute single cells

UID: 10387

Description
BISCUIT (Bayesian Inference for Single-cell ClUstering and ImpuTing) provides a method for the iterative normalization and cluster of single-cell gene RNA-seq expression data. BISCUIT eases clustering of cells based on similar gene expression after correcting technical variation. The software uses a Bayesian model and employs a model driven by covariance structures for the normalization and the input of data. These functionalities are appropriate to work on tumor heterogeneity and other primary tissue to understand novel cell types.
Subject(s)
Access via GitHub

Code and installation instructions for application

Access Restrictions
Free to All
Access Instructions
Code files are available for viewing, download, or clone through GitHub, including list of dependencies and installation instructions in the README.md
Associated Publications
Data Type
Dataset Format(s)
R
Data Catalog Record Updated
2019-11-12