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.
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Access via GitHub
Code and installation instructions for application
- Access Restrictions
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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
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