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  "Title": "Analyze Single Molecule Spatial Omics Data Using the\nProbabilistic Index",
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  "Description": "Test for univariate and bivariate spatial patterns in\nspatial omics data with single-molecule resolution. The tests\nimplemented allow for analysis of nested designs and are\nautomatically calibrated to different biological specimens.\nTests for aggregation, colocalization, gradients and vicinity\nto cell edge or centroid are provided.",
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    "plotExplore",
    "plotTopResults",
    "plotWf",
    "pnhyper",
    "selfName",
    "sund",
    "writeToXlsx"
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        "y",
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      "table": true,
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      "file": "Eng.RData",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": false
    },
    {
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      "title": "Spatial transcriptomics data of Selaginella moellendorffii roots",
      "object": "Yang",
      "file": "Yang.RData",
      "class": [
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        "root",
        "section"
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    {
      "page": "addCell",
      "title": "Add cell boundaries and event-wise cell identifiers to a hyperframe.",
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      ]
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    {
      "page": "addDesign",
      "title": "Add design variables to hyperframe",
      "topics": [
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      ]
    },
    {
      "page": "addNuclei",
      "title": "Add nuclei to a hyperframe",
      "topics": [
        "addNuclei"
      ]
    },
    {
      "page": "addTabObs",
      "title": "Add tables with gene counts to the hyperframe, presort by gene and x-ccordinate and add design varibales",
      "topics": [
        "addTabObs"
      ]
    },
    {
      "page": "buildDataFrame",
      "title": "Extract a data frame for a certain gene and PI from a fitted object",
      "topics": [
        "buildDataFrame"
      ]
    },
    {
      "page": "buildFormula",
      "title": "Build a formula from different components",
      "topics": [
        "buildFormula"
      ]
    },
    {
      "page": "buildHyperFrame",
      "title": "Build a hyperframe containing all point patterns of an experiment.",
      "topics": [
        "buildHyperFrame",
        "buildHyperFrame,data.frame-method",
        "buildHyperFrame,list-method",
        "buildHyperFrame,matrix-method",
        "buildHyperFrame,SpatialExperiment-method"
      ]
    },
    {
      "page": "calcIndividualPIs",
      "title": "Calculate individual PI entries of a single point pattern",
      "topics": [
        "calcIndividualPIs"
      ]
    },
    {
      "page": "calcNNPI",
      "title": "Estimate the PI for nearest neighbour distances with the negative hypergeometric distribution",
      "topics": [
        "calcNNPI"
      ]
    },
    {
      "page": "calcWindowDistPI",
      "title": "Estimate the PI for the distance to a fixed object of interest, such as a cell wall or centroid",
      "topics": [
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      ]
    },
    {
      "page": "centerNumeric",
      "title": "Center numeric variables",
      "topics": [
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      ]
    },
    {
      "page": "checkFeatures",
      "title": "Check if features are present in hyperframe",
      "topics": [
        "checkFeatures"
      ]
    },
    {
      "page": "checkPi",
      "title": "Check if the required PI's are present in the object",
      "topics": [
        "checkPi"
      ]
    },
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      "page": "constructDesignVars",
      "title": "Check for or construct design matrix",
      "topics": [
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      ]
    },
    {
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      "title": "Convert windows to spatstat.geom owin format",
      "topics": [
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      ]
    },
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      "page": "crossdistWrapper",
      "title": "A wrapper for C-functions calculating cross-distance matrix fast",
      "topics": [
        "crossdistWrapper"
      ]
    },
    {
      "page": "Eng",
      "title": "Spatial transcriptomics data of mouse fibroblast cells",
      "topics": [
        "Eng",
        "EngRois"
      ]
    },
    {
      "page": "estGradients",
      "title": "Estimate gradients over multiple point patterns, and test for significance",
      "topics": [
        "estGradients",
        "estGradientsSingle",
        "getPvaluesGradient"
      ]
    },
    {
      "page": "estPis",
      "title": "Estimate probabilistic indices and add a variance weighting function.",
      "topics": [
        "addWeightFunction",
        "estPis",
        "estPisSingle"
      ]
    },
    {
      "page": "evalWeightFunction",
      "title": "Evaluate a variance weighting function",
      "topics": [
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      ]
    },
    {
      "page": "extractResults",
      "title": "Extract results from a list of fitted LMMs. For internal use mainly.",
      "topics": [
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      ]
    },
    {
      "page": "findEcdfsCell",
      "title": "Construct empirical cumulative distribution functions (ecdfs) for within-cell distances",
      "topics": [
        "findEcdfsCell"
      ]
    },
    {
      "page": "findOverlap",
      "title": "Find overlap between list of windows",
      "topics": [
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      ]
    },
    {
      "page": "fitGradient",
      "title": "Test for presence of gradient in a hyperframe of point patterns",
      "topics": [
        "fitGradient"
      ]
    },
    {
      "page": "fitLMMs",
      "title": "Fit linear (mixed) models for all probabilistic indices (PIs) and all genes",
      "topics": [
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        "fitLMMsSingle",
        "getResults"
      ]
    },
    {
      "page": "fitPiModel",
      "title": "Fit a linear model for an individual gene and PI combination",
      "topics": [
        "fitPiModel"
      ]
    },
    {
      "page": "fitSingleLmmModel",
      "title": "Take an existing frame, add outcome and weight and fit lmer model",
      "topics": [
        "fitSingleLmmModel"
      ]
    },
    {
      "page": "getCoordsMat",
      "title": "Extract coordinates from a point pattern or data frame",
      "topics": [
        "getCoordsMat"
      ]
    },
    {
      "page": "getDesignVars",
      "title": "Extract design variables from a hyperframe",
      "topics": [
        "getDesignVars",
        "getEventVars",
        "getPPPvars"
      ]
    },
    {
      "page": "getElement",
      "title": "Extract en element from a matrix or vector",
      "topics": [
        "getElement"
      ]
    },
    {
      "page": "getFeatures",
      "title": "Extract all unique and estimated features from an object",
      "topics": [
        "getFeatures"
      ]
    },
    {
      "page": "getGp",
      "title": "Get a gene pair from a vector or list",
      "topics": [
        "getGp"
      ]
    },
    {
      "page": "getHypFrame",
      "title": "Extract the hyperframe",
      "topics": [
        "getHypFrame"
      ]
    },
    {
      "page": "getPiAndWeights",
      "title": "Build a matrix with pi and weights",
      "topics": [
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      ]
    },
    {
      "page": "lm_from_wfit",
      "title": "Add compoments to a result from lm.wfit to make it a minimally valid lm object",
      "topics": [
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      "title": "Parallel processing with BiocParallel with load balancing",
      "topics": [
        "loadBalanceBplapply"
      ]
    },
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      "page": "makeDesignVar",
      "title": "Make design variable by combining different design variables",
      "topics": [
        "makeDesignVar"
      ]
    },
    {
      "page": "makePairs",
      "title": "An aux function to build gene pairs",
      "topics": [
        "makePairs"
      ]
    },
    {
      "page": "named.contr.sum",
      "title": "A version of contr.sum that retains names, a bit controversial but also clearer",
      "topics": [
        "named.contr.sum"
      ]
    },
    {
      "page": "NegHyper",
      "title": "Negative hypergeometric distribution (taken from orphaned extraDistr package)",
      "concept": [
        "Discrete",
        "Univariate"
      ],
      "topics": [
        "NegHyper",
        "pnhyper"
      ]
    },
    {
      "page": "nestRandom",
      "title": "Nest random effects within fixed variables, in case the names are the same",
      "topics": [
        "nestRandom"
      ]
    },
    {
      "page": "plotCells",
      "title": "Plot the n cells with highest abundance of a feature",
      "topics": [
        "plotCells"
      ]
    },
    {
      "page": "plotExplore",
      "title": "Plot a hyperframe with chosen features highlighted",
      "topics": [
        "plotExplore"
      ]
    },
    {
      "page": "plotTopResults",
      "title": "Plot the most significant findings for a certain PI",
      "topics": [
        "plotTopResults"
      ]
    },
    {
      "page": "plotWf",
      "title": "Plot the variance weighting function",
      "topics": [
        "plotWf"
      ]
    },
    {
      "page": "selfName",
      "title": "Name a character vector after itself",
      "topics": [
        "selfName"
      ]
    },
    {
      "page": "sortGp",
      "title": "Sort feature pairs alphabetically",
      "topics": [
        "sortGp"
      ]
    },
    {
      "page": "splitWindow",
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