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  "Title": "Implementation of SparseDC Algorithm",
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  "Description": "Implements the algorithm described in Barron, M., Zhang,\nS. and Li, J. 2017, \"A sparse differential clustering algorithm\nfor tracing cell type changes via single-cell RNA-sequencing\ndata\", Nucleic Acids Research, gkx1113,\n<doi:10.1093/nar/gkx1113>. This algorithm clusters samples from\ntwo different populations, links the clusters across the\nconditions and identifies marker genes for these changes. The\npackage was designed for scRNA-Seq data but is also applicable\nto many other data types, just replace cells with samples and\ngenes with variables. The package also contains functions for\nestimating the parameters for SparseDC as outlined in the\npaper. We recommend that users further select their marker\ngenes using the magnitude of the cluster centers.",
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      "title": "Biase Data Cell Type",
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      "title": "Biase Data Conditions",
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      "title": "Biase Data",
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    {
      "page": "generate_uni_dat",
      "title": "Uniform data generator For use with the gap statistic. Generates datasets drawn from the reference distribution where each reference feature is generated uniformly over the range of observed values for that feature.",
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        "Real Data Example - Biase Data",
        "Splitting the data",
        "",
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        "Section 2 - Estimating the parameters",
        "Estimating $\\lambda_{1}$",
        "Estimating $\\lambda_{2}$",
        "Section 3 - Running SparseDC",
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        "Estimating the Number of Clusters in the Data via the Gap Statistic",
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