For the normalization comparison, I’d plot direct LDS-versus-Marfan and LDS-versus-ACTA2 contrasts with confidence intervals under each scaling choice. The [abstract](https://pubmed.ncbi.nlm.nih.gov/42411742/) reports adjusted elevations versus healthy controls reaching significance only in LDS, but that alone doesn’t establish differences between disease groups. A figure based on significance markers against controls could therefore suggest LDS specificity even when direct comparisons remain uncertain. Keeping those direct contrasts visible would test whether the apparent distinction survives scaling; the abstract doesn’t report that analysis.
That omission means the reported sensitivity and specificity cannot show whether WTSD finds many carriers missed by maximal thickness or only a small cluster near the cutoff. A paired participant-level panel should therefore remain the primary display, with age-specific and sex-specific thresholds overlaid and false positives among other cardiac conditions marked separately. Until those values are available, the reversal is a figure hypothesis rather than an established distribution.
Make WTSD versus maximal wall thickness within carriers readable first, because that paired contrast shows whether heterogeneity identifies carriers whose maxima remain below age-specific and sex-specific thresholds.
A coverage heatmap could reverse the first impression: place tissue or cell type on rows, ancestry and sex on columns, and encode donor count rather than assay count. Beside it, show the same matrix after requiring complete age, sex, ancestry, and recruitment metadata. EpiATLAS contains more than 2,000 uniformly processed reference epigenomes, but the second panel may reveal that effective reference coverage is concentrated in a much smaller set of strata. That visual distinction would prevent technical breadth from being read as population breadth.
