A robust and outlier-aware method for testing differential tissue composition from single-cell data. This model can infer changes in tissue composition and heterogeneity, and can produce realistic data simulations based on any existing dataset. This model can also transfer knowledge from a large set of integrated datasets to increase accuracy further.
Package details |
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Bioconductor views | Bayesian DifferentialExpression Regression SingleCell |
Maintainer | |
License | GPL-3 |
Version | 2.1.5 |
URL | https://github.com/MangiolaLaboratory/sccomp |
Package repository | View on GitHub |
Installation |
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