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  "Title": "PHATE - Potential of Heat-Diffusion for Affinity-Based\nTransition Embedding",
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  "Description": "PHATE is a tool for visualizing high dimensional\nsingle-cell data with natural progressions or trajectories.\nPHATE uses a novel conceptual framework for learning and\nvisualizing the manifold inherent to biological systems in\nwhich smooth transitions mark the progressions of cells from\none state to another. To see how PHATE can be applied to\nsingle-cell RNA-seq datasets from hematopoietic stem cells,\nhuman embryonic stem cells, and bone marrow samples, check out\nour publication in Nature Biotechnology at\n<doi:10.1038/s41587-019-0336-3>.",
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      "title": "KMeans on the PHATE potential Clustering on the PHATE operator as introduced in Moon et al. This is similar to spectral clustering.",
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