scHOT_estimatePvalues {scHOT} | R Documentation

## scHOT_estimatePvalues

### Description

Estimate p-values based on already run permutation tests

### Usage

    scHOT_estimatePvalues(
      scHOT,
      usenperm_estimate = FALSE,
      nperm_estimate = 10000,
      maxDist = 0.1,
      plot = FALSE,
      verbose = FALSE
    )

### Arguments

`scHOT` | A scHOT object
`usenperm_estimate` | Logical (default FALSE) if number of neighbouring permutations should be used, or if difference of global higher order statistic should be used
`nperm_estimate` | Number of neighbouring permutations to use for p-value estimation
`maxDist` | max difference of global higher order statistic to use for p-value estimation (default 0.1)
`plot` | A logical input indicating whether the results are plotted
`verbose` | A logical input indicating whether the intermediate steps will be printed

### Value

scHOT A scHOT object with results stored in scHOT_output slot

### Examples

     data(MOB_subset)
     sce_MOB_subset <- MOB_subset$sce_MOB_subset
     scHOT_spatial <- scHOT_buildFromSCE(sce_MOB_subset,
                                         assayName = "logcounts",
                                        positionType = "spatial",
                                         positionColData = c("x", "y"))
    pairs <- matrix(c("Arrb1", "Mtor", "Dnm1l", "Gucy1b3"), ncol = 2, byrow = TRUE)
    rownames(pairs) <- apply(pairs,1,paste0,collapse = "_")

    scHOT_spatial <- scHOT_addTestingScaffold(scHOT_spatial, pairs)

    scHOT_spatial <- scHOT_setWeightMatrix(scHOT_spatial,
                                           positionColData = c("x","y"),
                                            positionType = "spatial",
                                            nrow.out = NULL,
                                            span = 0.05)
    scHOT_spatial <- scHOT_calculateGlobalHigherOrderFunction(
      scHOT_spatial,
      higherOrderFunction = weightedSpearman,
      higherOrderFunctionType = "weighted")
    scHOT_spatial <- scHOT_setPermutationScaffold(scHOT_spatial,
                                                  numberPermutations = 100)
    scHOT_spatial <- scHOT_calculateHigherOrderTestStatistics(
      scHOT_spatial,
      higherOrderSummaryFunction = sd)

    scHOT_spatial <- scHOT_performPermutationTest(
      scHOT_spatial,
      verbose = TRUE,
      parallel = FALSE)

    scHOT_spatial <- scHOT_estimatePvalues(scHOT_spatial)

[Package scHOT version 1.6.0 Index]