saeyslab/ViVAE
Single-cell dimensionality reduction toolkit
ViVAE is a toolkit that helps biologists and researchers analyze complex single-cell data, such as single-cell RNA sequencing (scRNA-seq) or cytometry data. It takes your raw single-cell measurements and transforms them into simplified, lower-dimensional visualizations that preserve important cellular relationships and structures, even for data with complex trajectories or batch effects. This is ideal for scientists working with large single-cell datasets who need clear, interpretable visualizations to understand cell populations and differentiation paths.
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Use this if you need to visualize high-dimensional single-cell data while ensuring that the underlying biological structures, like cell trajectories or rare cell populations, are accurately represented.
Not ideal if you are looking for a general-purpose dimensionality reduction tool for non-biological data, or if you primarily work with very small datasets where the overhead of a deep learning model isn't justified.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Aug 11, 2025
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