bioconductor-lemur
Latent Embedding Multivariate Regression
Latent Embedding Multivariate Regression
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Fit a latent embedding multivariate regression (LEMUR) model to multi-condition single-cell data. The model provides a parametric description of single-cell data measured with treatment vs. control or more complex experimental designs. The parametric model is used to (1) align conditions, (2) predict log fold changes between conditions for all cells, and (3) identify cell neighborhoods with consistent log fold changes. For those neighborhoods, a pseudobulked differential expression test is conducted to assess which genes are significantly changed.
Summary
Latent Embedding Multivariate Regression
Last Updated
Dec 21, 2024 at 05:40
License
MIT + file LICENSE
Total Downloads
1.7K
Supported Platforms