QC heatmap of Jensen-Shannon Divergence across markers and samples

Displays the per-marker JSD quality metric as a clustered heatmap, optionally annotated with the proportion of the signal GMM component. Accepts a named list of BgnormResult objects (single sample), a named list of such lists (multiple samples), or a SummarizedExperiment / SpatialExperiment with bgnorm results in metadata(results)$bgnorm_results.

Usage

plot_jsd_heatmap(
  results,
  cluster_rows = TRUE,
  cluster_cols = TRUE,
  show_tissue_positivity = TRUE
)

Arguments

results

A named list of BgnormResult objects (single sample), a named list of such lists (multiple samples), a named list of QPTIFFImage objects returned by bgnorm_pixels (one per sample; all must share the same channel names), a single QPTIFFImage, or a SummarizedExperiment / SpatialExperiment.

cluster_rows

Logical; cluster samples (rows)? Default TRUE.

cluster_cols

Logical; cluster markers (columns)? Default TRUE.

show_tissue_positivity

Logical; overlay tissue positivity as circles on the heatmap? Circle area is proportional to the tissue positivity (\(\pi_3 / (\pi_2 + \pi_3)\) for three-component models; \(\pi_2\) for two-component models). Circle colour indicates JSD quality: red (JSD < 0.1, low), orange (0.1-0.2, moderate), white (\(\geq\) 0.2, good). Default TRUE.

Value

A ggplot object.

See also

bgnorm_pixels, bgnorm_sce

Examples

path <- system.file("extdata", "PA_HNC_sample.ome.tiff", package = "bgnormR")
img  <- read_qptiff(path)
#> Reading TIFF directory structure ...
#> Reading OME-TIFF metadata ...
#> Reading IFD page layouts ...
#> Loading 5 channel(s) ...
#> Loading 5 channel(s) ...
res  <- bgnorm_pixels(img, sample_prop = 0.1)
plot_jsd_heatmap(res)


# Multi-sample comparison (pass a named list)
plot_jsd_heatmap(list(sample_A = res, sample_B = res))