Compute observation statistic for permutation framework
Source:R/compute_permp.R
compute_observation.Rd
Compute observation statistic for permutation framework
Usage
compute_observation(
data,
cluster_info,
correlation_method = "pearson",
all_genes = all_genes,
bin_type,
bin_param,
w_x,
w_y
)
Arguments
- data
A list of matrices containing the coordinates of transcripts.
- 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).
- 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.- all_genes
A vector of strings giving the name of the genes you want to test correlation for.
- 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 thebin_type
is "hexagonal", this will be a number giving the side length of hexagons. Positive numbers only.- 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.
Value
A named list with the following components
obs.stat
A matrix contains the observation statistic for every gene and every cluster. Each row refers to a gene, and each column refers to a cluster
gene_mt
contains the transcript count in each grid. Each row refers to a grid, and each column refers to a gene.