rockdeme/chrysalis
Powerful and lightweight package to identify tissue compartments in spatial transcriptomics datasets.
This project helps biological researchers identify and visualize distinct tissue compartments within their spatial transcriptomics datasets. By analyzing gene expression data from tissue samples, it pinpoints unique regions like germinal centers or T cell compartments and shows their specific gene signatures. Scientists working with spatial gene expression will find this useful for understanding tissue organization.
No commits in the last 6 months.
Use this if you need to automatically identify and map different tissue regions and their associated gene expression patterns from your spatial transcriptomics data without needing external reference maps.
Not ideal if you are working with non-spatial transcriptomics data or if you already have clear, pre-defined tissue regions and only need to analyze gene expression within them.
Stars
18
Forks
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Language
Jupyter Notebook
License
BSD-3-Clause
Category
Last pushed
Jun 09, 2025
Commits (30d)
0
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