xinglab-ai/genomap
Cartography of Genomic Interactions Enables Deep Analysis of Single-Cell Expression Data (Nature Communications, 2023)
This project helps single-cell biologists and computational biologists analyze complex gene expression data by transforming it into image-like 'genomaps'. It takes high-dimensional single-cell gene expression datasets and outputs visualizations, clusters, cell annotations, and integrated multi-omic data, providing a clearer understanding of cellular states and trajectories. This is ideal for researchers working with single-cell genomics who need advanced analytical tools.
No commits in the last 6 months. Available on PyPI.
Use this if you need to deeply analyze single-cell gene expression data, perform robust cell clustering, visualize data, identify gene signatures, or integrate multiple omics datasets with improved accuracy.
Not ideal if your primary data is not gene expression or if you require an analysis that doesn't benefit from spatial mapping of genomic interactions.
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Python
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May 27, 2024
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