MICS-Lab/scyan
Biology-driven deep generative model for cell-type annotation in cytometry. Scyan is an interpretable model that also corrects batch-effect and can be used for debarcoding or population discovery.
This helps biologists and researchers rapidly identify and annotate different cell types from cytometry data, such as flow cytometry or mass cytometry. You input raw cell expression data, and it outputs clear, interpretable cell population labels, correcting for variations between experiments. Researchers in immunology, oncology, or cell biology who work with single-cell data will find this useful.
No commits in the last 6 months. Available on PyPI.
Use this if you need to automatically and accurately classify cell populations from cytometry data, especially when dealing with batch effects or wanting to discover new cell types without extensive manual gating or training labels.
Not ideal if your primary need is general-purpose data visualization or statistical analysis unrelated to single-cell cytometry annotation.
Stars
42
Forks
2
Language
Python
License
BSD-3-Clause
Category
Last pushed
Nov 22, 2024
Commits (30d)
0
Dependencies
9
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