CONCORD¶
Revealing the underlying cell-state landscape from single-cell data requires overcoming the critical obstacles of batch integration, denoising, and dimensionality reduction. We present CONCORD, a unified framework that simultaneously addresses these challenges within a single self-supervised model. At its core, CONCORD implements a unified probabilistic sampling strategy that corrects batch effects via dataset-aware sampling and enhances biological resolution through hard-negative sampling.
homepage: https://github.com/Gartner-Lab/Concord
| version | versionsuffix | toolchain |
|---|---|---|
1.0.13 |
-CUDA-12.1.1 |
foss/2023a |
1.0.13 |
foss/2023a |
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