Batch create layer classifications for multiple clusters and optionally generate individual plots for each cluster.
Usage
create_all_layers(
df,
clusters = NULL,
k = 6,
max_dist = NULL,
intermediate_quantile = 0.5,
coord_cols = c("x", "y"),
cluster_col = "cluster"
)Arguments
- df
A data.frame containing at least coordinate and cluster columns.
- clusters
Optional vector of cluster labels to process. If `NULL`, all unique clusters are used.
- k
Integer. Number of nearest neighbors to consider. Default is 6.
- max_dist
Optional numeric. Maximum Euclidean distance for neighbors.
- intermediate_quantile
Numeric between 0 and 1. The quantile of distances to border used to define the intermediate layer threshold. Default is 0.5 (median).
- coord_cols
Character vector of length 2 giving the coordinate column names. Default is `c("x","y")`.
- cluster_col
Character. Name of the column containing cluster labels. Default is `"cluster"`.
Examples
data("visiumHD_16um_simulated_spe", package = "Battlefield")
spe <- visiumHD_16um_simulated_spe
df <- data.frame(
spot_id = colnames(spe),
x = spatialCoords(spe)[, 1],
y = spatialCoords(spe)[, 2],
cluster = colData(spe)$cluster
)
#> Error in spatialCoords(spe): could not find function "spatialCoords"
all_layers <- create_all_layers(df, k = 6, intermediate_quantile = 0.5)
#> Error in create_all_layers(df, k = 6, intermediate_quantile = 0.5): all(coord_cols %in% colnames(df)) is not TRUE
head(all_layers)
#> Error: object 'all_layers' not found