Generate connectivity matrix — generate

Based on the radius with the lowest TopKAT p-value, compute a connections matrix that shows how many edges are between cells of each type at the simplicial complex constructed based on this radius.

Usage

generate_connectivity(images.df, threshold, type.column, unique.types)

Arguments

images.df: A data.frame containing the image information. See details.
threshold: Radius to generate connectivity for
type.column: The name of the column in images.df that contains the cell types
unique.types: Vector of unique cell types in the type.column

Value

Returns a connectivity matrix of dimension \(n\times n\) where \(n\) is the number of cell types, i.e. the length of unique.types

Details

images.df should contain a PID column indicating which sample each image corresponds to. It should also contain columns x and y indicating the location of each cell. Each row in images.df corresponds to a cell within each image. See the package vignettes for an example of the structure.

This function may take several minutes to run and does require a substantial amount of memory. If the memory limit is reached, consider running mem.maxVSize(vsize = x) and specify x to a large value.

Examples

require(magrittr)
#> Loading required package: magrittr
conmat <- generate_connectivity(data1.df %>% dplyr::filter(PID == 1), threshold = 10,
                                type.column = "type", unique.types = unique(data1.df$type))