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Add info about how spots overlap among capture areas

Source: R/add_overlap_info.R
add_overlap_info.Rd

Given a SpatialExperiment-class and column name in its colData, return a modified copy of the SpatialExperiment with additional colData columns: spe$exclude_overlapping and spe$overlap_key.

Usage

add_overlap_info(spe, metric_name)

Arguments

spe

A SpatialExperiment-class with colData(spe) columns array_row, array_col, key, and capture_area.

metric_name

character(1) in colnames(colData(spe)), where spots belonging to the capture area with highest average value for the metric take precedence over other spots.

Value

A SpatialExperiment object with additional colData columns spe$exclude_overlapping and spe$overlap_key.

Details

spe$exclude_overlapping is TRUE for spots with a higher-quality overlapping capture area and FALSE otherwise. vis_clus onlydisplays FALSE spots to prevent overplotting in regions of overlap. spe$overlap_key gives comma-separated strings containing the keys of any overlapping spots, and is the empty string otherwise.

Author

Nicholas J. Eagles

Examples

if (!exists("spe")) {
    spe <- spatialLIBD::fetch_data(type = "visiumStitched_brain_spe")
}
#> 2024-11-08 18:52:21.855036 loading file /github/home/.cache/R/BiocFileCache/6c1f1cbefd45_visiumStitched_brain_spe.rds%3Frlkey%3Dnq6a82u23xuu9hohr86oodwdi%26dl%3D1

#    Find the mean of the 'sum_umi' metric by capture area to understand
#    which capture areas will be excluded in regions of overlap
SummarizedExperiment::colData(spe) |>
    dplyr::as_tibble() |>
    dplyr::group_by(capture_area) |>
    dplyr::summarize(mean_sum_umi = mean(sum_umi))
#> # A tibble: 3 × 2
#>   capture_area  mean_sum_umi
#>   <fct>                <dbl>
#> 1 V13B23-283_A1        2075.
#> 2 V13B23-283_C1        1188.
#> 3 V13B23-283_D1        2083.

spe <- add_overlap_info(spe, "sum_umi")

#    See how many spots were excluded by capture area
table(spe$exclude_overlapping, spe$capture_area)
#>        
#>         V13B23-283_A1 V13B23-283_C1 V13B23-283_D1
#>   FALSE          3920          4367          4596
#>   TRUE           1032            50             0

#    Examine how data about overlapping spots is stored (for the first
#    few spots with overlap)
head(spe$overlap_key[spe$overlap_key != ""])
#> [1] "TCAGAACGGCGGTAAT-1_V13B23-283_D1,TGCCCGATAGTTAGAA-1_V13B23-283_D1"
#> [2] "CGACTTGCCGGGAAAT-1_V13B23-283_D1,TCATGAAGCGCTGCAT-1_V13B23-283_D1"
#> [3] "CCTTAAGTACGCAATT-1_V13B23-283_D1"                                 
#> [4] "GAAGCCACTGATTATG-1_V13B23-283_D1"                                 
#> [5] "ACTCAAGTGCAAGGCT-1_V13B23-283_D1"                                 
#> [6] "GGCCTGCTTCTCCCGA-1_V13B23-283_D1"