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  "Title": "Marker Enrichment Modeling (MEM)",
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  "Description": "MEM, Marker Enrichment Modeling, automatically generates\nand displays quantitative labels for cell populations that have\nbeen identified from single-cell data. The input for MEM is a\ndataset that has pre-clustered or pre-gated populations with\ncells in rows and features in columns. Labels convey a list of\nmeasured features and the features' levels of relative\nenrichment on each population. MEM can be applied to a wide\nvariety of data types and can compare between MEM labels from\nflow cytometry, mass cytometry, single cell RNA-seq, and\nspectral flow cytometry using RMSD.",
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  "_realowner": "bioc",
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      "title": "MEM matrix",
      "object": "MEM_matrix",
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        "array"
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        "CD117",
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        "CD4",
        "CD8",
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      "tojson": true
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      "title": "Build heatmaps",
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      "title": "Marker Enrichment Modeling",
      "topics": [
        "MEM"
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      "title": "MEM matrix",
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