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  1. CELESTA CELESTA Public

    Automate unsupervised machine learning cell type identification using both protein expressions and cell spatial neighborhood information for multiplexed in situ imaging data. No training dataset wi…

    R 39 13

  2. remi remi Public

    The REMI package is written in R and is designed to predict ligand receptor interactions within a microenvironment given RNA-sequencing data. It regularizes communities of ligand and receptors that…

    HTML 3 1

  3. Spatial_Permutation_and_Normalization Spatial_Permutation_and_Normalization Public

    Permutation analysis and normalization strategy for the colocatome paper.

    R 3 1

  4. HNSCC-atlas-alignment HNSCC-atlas-alignment Public

    Single-cell alignment for scRNA-seq and CITE-seq U54 data

    Python 2

  5. dcspomic dcspomic Public

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  6. spomic spomic Public

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