gao-lab/GLUE

Graph-linked unified embedding for single-cell multi-omics data integration

57
/ 100
Established

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.

single-cell biology genomics transcriptomics bioinformatics cell-type-identification
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 21 / 25

How are scores calculated?

Stars

456

Forks

70

Language

Python

License

MIT

Last pushed

Feb 09, 2026

Commits (30d)

0

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