gao-lab/PASSAGE
Phenotype Associated Spatial Signature Analysis with Graph-based Embedding
This tool helps researchers analyze spatial transcriptomics data to understand how gene expression patterns are linked to specific disease phenotypes. You input spatially-resolved gene expression data and phenotype information, and it outputs identified gene signatures and their spatial distributions associated with those phenotypes. This is designed for biologists, geneticists, and medical researchers studying disease mechanisms.
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Use this if you need to uncover the spatially organized molecular characteristics that define different biological conditions or disease states from spatial transcriptomics data.
Not ideal if you are working with single-cell RNA sequencing data without spatial context, or if your primary goal is general cell type identification rather than phenotype association.
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Jupyter Notebook
License
MIT
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Last pushed
Mar 05, 2025
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