gao-lab/GLUE
Graph-linked unified embedding for single-cell multi-omics data integration
This project helps single-cell biologists and researchers integrate different types of single-cell omics data, such as genomics and transcriptomics, to get a unified view of cell states. It takes in various single-cell datasets, finds relationships between them, and outputs a combined representation that helps identify cell types and understand biological processes more accurately. This is designed for scientists analyzing complex biological data at the single-cell level.
456 stars.
Use this if you need to combine and analyze multiple single-cell omics datasets to gain a more comprehensive understanding of cellular heterogeneity and function.
Not ideal if you are working with bulk omics data or if your primary goal is not single-cell data integration.
Stars
456
Forks
70
Language
Python
License
MIT
Category
Last pushed
Feb 09, 2026
Commits (30d)
0
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