Compute permutation statistics for permutation framework

Usage

compute_permutation(
  cluster_info,
  perm.size = 1000,
  correlation_method = "pearson",
  bin_type,
  bin_param,
  n_cores = 1,
  w_x,
  w_y,
  gene_mt,
  cluster_names
)

Arguments

cluster_info: A dataframe/matrix containing the centroid coordinates and cluster label for each cell.The column names should include "x" (x coordinate), "y" (y coordinate), and "cluster" (cluster label).
perm.size: A positive number specifying permutation times
correlation_method: A parameter pass to cor, indicating which correlation coefficient is to be computed. One of "pearson" (default), "kendall", or "spearman": can be abbreviated.
bin_type: A string indicating which bin shape is to be used for vectorization. One of "square" (default), "rectangle", or "hexagon".
bin_param: A numeric vector indicating the size of the bin. If the bin_type is "square" or "rectangle", this will be a vector of length two giving the numbers of rectangular quadrats in the x and y directions. If the bin_type is "hexagonal", this will be a number giving the side length of hexagons. Positive numbers only.
n_cores: A positive number specifying number of cores used for parallelizing permutation testing. Default is one core (sequential processing).
w_x: a numeric vector of length two specifying the x coordinate limits of enclosing box.
w_y: a numeric vector of length two specifying the y coordinate limits of enclosing box.
gene_mt: A matrix contains the transcript count in each grid. Each row refers to a grid, and each column refers to a gene.
cluster_names: A list of strings giving the name and order of the clusters

Value

A matrix with permutation statistics