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  "Description": "Wires together large collections of single-cell RNA-seq\ndatasets, which allows for both the identification of recurrent\ncell clusters and the propagation of information between\ndatasets in multi-sample or atlas-scale collections. 'Conos'\nfocuses on the uniform mapping of homologous cell types across\nheterogeneous sample collections. For instance, users could\ninvestigate a collection of dozens of peripheral blood samples\nfrom cancer patients combined with dozens of controls, which\nperhaps includes samples of a related tissue such as lymph\nnodes. This package interacts with data available through the\n'conosPanel' package, which is available in a 'drat'\nrepository. To access this data package, see the instructions\nat <https://github.com/kharchenkolab/conos>. The size of the\n'conosPanel' package is approximately 12 MB.",
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  "Copyright": "See the file COPYRIGHTS for various conos copyright details",
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    "getPca",
    "getPerCellTypeDE",
    "getRawCountMatrix",
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    "rawMatricesWithCommonGenes",
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    "saveDEasJSON",
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      "page": "basicSeuratProc",
      "title": "Create and preprocess a Seurat object",
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      "page": "bestClusterThresholds",
      "title": "Find threshold of cluster detectability",
      "topics": [
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      ]
    },
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      "page": "bestClusterTreeThresholds",
      "title": "Find threshold of cluster detectability in trees of clusters",
      "topics": [
        "bestClusterTreeThresholds"
      ]
    },
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      "page": "buildWijMatrix",
      "title": "Rescale the weights in an edge matrix to match a given perplexity.",
      "topics": [
        "buildWijMatrix",
        "buildWijMatrix.CsparseMatrix",
        "buildWijMatrix.TsparseMatrix"
      ]
    },
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      "page": "Conos",
      "title": "Conos R6 class",
      "topics": [
        "Conos"
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      "title": "Convert Conos object to Pagoda2 object",
      "topics": [
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    },
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      "title": "Set edge matrix edgeMat with certain values on sample",
      "topics": [
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        "edgeMat,Pagoda2-method",
        "edgeMat,Seurat-method",
        "edgeMat,seurat-method",
        "edgeMat<-",
        "edgeMat<-,Pagoda2-method",
        "edgeMat<-,Seurat-method",
        "edgeMat<-,seurat-method"
      ]
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      "topics": [
        "estimateWeightEntropyPerCell"
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    },
    {
      "page": "findSubcommunities",
      "title": "Increase resolution for a specific set of clusters",
      "topics": [
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      "title": "Compare two cell types across the entire panel",
      "topics": [
        "getBetweenCellTypeCorrectedDE"
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    },
    {
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      "title": "Compare two cell types across the entire panel",
      "topics": [
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      ]
    },
    {
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      "title": "Access cell names from sample",
      "topics": [
        "getCellNames",
        "getCellNames,Conos-method",
        "getCellNames,Pagoda2-method",
        "getCellNames,Seurat-method",
        "getCellNames,seurat-method"
      ]
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      "page": "getClustering",
      "title": "Access clustering from sample",
      "topics": [
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        "getClustering,Conos-method",
        "getClustering,Pagoda2-method",
        "getClustering,Seurat-method",
        "getClustering,seurat-method"
      ]
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    {
      "page": "getCountMatrix",
      "title": "Access count matrix from sample",
      "topics": [
        "getCountMatrix",
        "getCountMatrix,Pagoda2-method",
        "getCountMatrix,Seurat-method",
        "getCountMatrix,seurat-method"
      ]
    },
    {
      "page": "getEmbedding",
      "title": "Access embedding from sample",
      "topics": [
        "getEmbedding",
        "getEmbedding,Conos-method",
        "getEmbedding,Pagoda2-method",
        "getEmbedding,Seurat-method",
        "getEmbedding,seurat-method"
      ]
    },
    {
      "page": "getGeneExpression",
      "title": "Access gene expression from sample",
      "topics": [
        "getGeneExpression",
        "getGeneExpression,Conos-method",
        "getGeneExpression,Pagoda2-method",
        "getGeneExpression,Seurat-method",
        "getGeneExpression,seurat-method"
      ]
    },
    {
      "page": "getGenes",
      "title": "Access genes from sample",
      "topics": [
        "getGenes",
        "getGenes,Conos-method",
        "getGenes,Pagoda2-method",
        "getGenes,Seurat-method",
        "getGenes,seurat-method"
      ]
    },
    {
      "page": "getOverdispersedGenes",
      "title": "Access overdispersed genes from sample",
      "topics": [
        "getOverdispersedGenes",
        "getOverdispersedGenes,Conos-method",
        "getOverdispersedGenes,Pagoda2-method",
        "getOverdispersedGenes,Seurat-method",
        "getOverdispersedGenes,seurat-method"
      ]
    },
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      "page": "getPca",
      "title": "Access PCA from sample",
      "topics": [
        "getPca",
        "getPca,Pagoda2-method",
        "getPca,Seurat-method",
        "getPca,seurat-method"
      ]
    },
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      "page": "getPerCellTypeDE",
      "title": "Do differential expression for each cell type in a conos object between the specified subsets of apps",
      "topics": [
        "getPerCellTypeDE"
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    },
    {
      "page": "getRawCountMatrix",
      "title": "Access raw count matrix from sample",
      "topics": [
        "getRawCountMatrix",
        "getRawCountMatrix,Conos-method",
        "getRawCountMatrix,Pagoda2-method",
        "getRawCountMatrix,Seurat-method",
        "getRawCountMatrix,seurat-method"
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    },
    {
      "page": "getSampleNamePerCell",
      "title": "Retrieve sample names per cell",
      "topics": [
        "getSampleNamePerCell"
      ]
    },
    {
      "page": "greedyModularityCut",
      "title": "Performs a greedy top-down selective cut to optmize modularity",
      "topics": [
        "greedyModularityCut"
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      "title": "Utility function to generate a pagoda2 app from a conos object",
      "topics": [
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      "title": "Plots barplots per sample of composition of each pagoda2 application based on selected clustering",
      "topics": [
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    },
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      "page": "plotClusterBoxPlotsByAppType",
      "title": "Generate boxplot per cluster of the proportion of cells in each celltype",
      "topics": [
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      "title": "Plot fraction of variance explained by the successive reduced space components (PCA, CPCA)",
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