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Select core (non-interface) spots for a directed pair

Source: R/R-border.R
select_core_spots.Rd

This function selects core (non-interface) spots from a cluster that match the count of border spots for a specific directed pair. The `mode` value is read from the `border_df` dataframe for this cluster/interface pair. If multiple mode values exist in border_df for the pair, a warning is printed and the first value is used.

Usage

select_core_spots(
  df,
  border_df,
  cluster,
  interface,
  mode = "both",
  coord_cols = c("x", "y"),
  cluster_col = "cluster"
)

Arguments

df

A data.frame containing at least the coordinate columns and a cluster label column.

border_df

A data.frame of border spots from [build_all_borders()], containing columns `spot_id`, `cluster`, `interface`, `directed_pair`, etc.

cluster

Character. Label of the cluster from which to select inner spots.

interface

Character. Label of the target cluster for the directed pair.

mode

Character. One of "inner", "outer", or "both". Controls which mode values from border_df to use when counting border spots. When mode="both", both "inner" and "outer" mode rows from border_df are used. Default is "both".

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"`.

Value

A data.frame of sampled core spots from `cluster`, with all columns from `df` plus `interface` annotation.

Details

For example with `cluster="1"` and `interface="2"`: - If mode in df is "inner": counts only border spots from 1→2 - If mode in df is "outer": counts only border spots from 2→1 - If mode in df is "both": counts border spots from both 1→2 AND 2→1

This returns N random inner spots from the cluster, where N equals the border count.

Steps:

  1. Counts directed border spots based on `mode` parameter.

  2. Gets all spots in `cluster` that are not at any border.

  3. Randomly samples the same number of core spots as the border count.

  4. Returns these sampled core spots with `interface` annotation.

If not enough core spots exist to match the border count, all available core spots are returned with a warning.

Examples

# Create synthetic spatial transcriptomics data with 3 clusters
df_ex <- data.frame(
  spot_id = paste0("spot_", seq_len(300)),
  x = rnorm(300),
  y = rnorm(300),
  cluster = sample(c("A", "B", "C"), 300, replace = TRUE)
)

# Step 1: Identify all border spots between clusters
all_borders <- build_all_borders(df_ex, k = 6)

# Step 2: Select core spots for the directed pair A→B
# matching the number of border spots found
cores_inner <- select_core_spots(
  df_ex,
  border_df = all_borders,
  cluster = "A",
  interface = "B",
  mode = "inner"
)
#> Not enough core spots for pair(cluster=A, interface=B, mode=inner). Requested:85, Available:0. Returning all available.
#> Error in `$<-.data.frame`(`*tmp*`, "interface", value = "B"): replacement has 1 row, data has 0
head(cores_inner)
#> Error: object 'cores_inner' not found

# Step 3: Select core spots considering both directions (A→B AND B→A)
cores_both <- select_core_spots(
  df_ex,
  border_df = all_borders,
  cluster = "A",
  interface = "B",
  mode = "both"
)
#> Not enough core spots for pair(cluster=A, interface=B, mode=both). Requested:170, Available:0. Returning all available.
#> Error in `$<-.data.frame`(`*tmp*`, "interface", value = "B"): replacement has 1 row, data has 0
head(cores_both)
#> Error: object 'cores_both' not found