SpicyResults-class {spicyR} | R Documentation

## Performs spatial tests on spatial cytometry data.

### Description

Performs spatial tests on spatial cytometry data.

### Usage

    spicy(
      cells,
      condition = NULL,
      subject = NULL,
      covariates = NULL,
      from = NULL,
      to = NULL,
      dist = NULL,
      integrate = TRUE,
      nsim = NULL,
      verbose = TRUE,
      weights = TRUE,
      window = "convex",
      window.length = NULL,
      BPPARAM = BiocParallel::SerialParam(),
      sigma = NULL,
      Rs = NULL,
      minLambda = 0.05,
      fast = TRUE,
      ...
    )

### Arguments

`cells` | A SegmentedCells or data frame that contains at least the variables x and y, giving the location coordinates of each cell, and cellType.
`condition` | Vector of conditions to be tested corresponding to each image if cells is a data frame.
`subject` | Vector of subject IDs corresponding to each image if cells is a data frame.
`covariates` | Vector of covariate names that should be included in the mixed effects model as fixed effects.
`from` | vector of cell types which you would like to compare to the to vector
`to` | vector of cell types which you would like to compare to the from vector
`dist` | The distance at which the statistic is obtained.
`integrate` | Should the statistic be the integral from 0 to dist, or the value of the L curve at dist.
`nsim` | Number of simulations to perform. If empty, the p-value from lmerTest is used.
`verbose` | logical indicating whether to output messages.
`weights` | logical indicating whether to include weights based on cell counts.
`window` | Should the window around the regions be 'square', 'convex' or 'concave'.
`window.length` | A tuning parameter for controlling the level of concavity when estimating concave windows.
`BPPARAM` | A BiocParallelParam object.
`sigma` | A numeric variable used for scaling when fitting inhomogeneous L-curves.
`Rs` | A vector of the radii that the measures of association should be calculated.
`minLambda` | Minimum value for density for scaling when fitting inhomogeneous L-curves.
`fast` | A logical describing whether to use a fast approximation of the inhomogeneous L-curves.
`...` | Other options to pass to bootstrap.

### Value

Data frame of p-values.

### Examples

    data("diabetesData")

    # Test with random effect for patient on only one pairwise combination of cell types.
    spicy(diabetesData, condition = "stage", subject = "case",
          from = "Tc", to = "Th")

    # Test all pairwise combination of cell types without random effect of patient.
    #spicyTest <- spicy(diabetesData, condition = "stage", subject = "case")

    # Test all pairwise combination of cell types with random effect of patient.
    #spicy(diabetesData, condition = "condition", subject = "subject")

    # Test all pairwise combination of cell types with random effect of patient using
    # a bootstrap to calculate significance.
    #spicy(diabetesData, condition = "stage", subject = "case", nsim = 10000)

[Package spicyR version 1.4.0 Index]