Promoter DNA Methylation Metrics and Gene Expression in Human CD3+ T Cells: Sensitivity to Analytical Choices

Background/Objectives: Promoter DNA methylation is conventionally summarised as a regional mean. Two alternatives have been proposed to capture information the mean discards: the concurrence ratio derived from partially methylated bisulfite reads (CAMDA) and single-CpG Shannon (β-) entropy. Benchmarks of such metrics typically report one coefficient per metric on a single gene set at a single aggregation scale. We asked how far that comparison depends on analytical choices that are rarely reported. Methods: Matched whole-genome bisulfite sequencing (WGBS) and RNA-seq from one donor of human CD3+ T cells were analysed. Promoter windows spanning -1000 to +500 bp around the transcription start site (TSS) were divided into fifteen 100 bp bins; all three metrics were computed on an identical CpG set and correlated with log₂(FPKM) by Spearman's ρ. The comparison was repeated across annotation source, quantification level, coverage threshold, aggregation scheme, the treatment of zero-expression transcripts and CpG island status, with metric differences assessed by paired bootstrap over promoters and over chromosomes. Results: Across a grid of five analytical choices, the mean methylation coefficient ranged from -0.145 to -0.593 and the ordering of the metrics reversed between configurations. At the 100 bp bin scale, the largest difference between metrics was 0.037; aggregating the same CpGs to the whole promoter opened differences of up to 0.31, so the apparent superiority of a metric is itself a function of the aggregation scale. CAMDA exceeded the regional mean consistently but modestly, with the advantage largest in distal upstream bins and indistinguishable from zero adjacent to the TSS. β-Entropy is a strictly monotone function of the folded measure 1 - 2|β - 0.5|; at the 100 bp scale, the mean of per-CpG entropy tracked the folding transform of regional mean methylation to within 0.002 in every bin, while at the whole-promoter scale, the two separated by 0.041. Within CpG islands, the regional mean weakened (ρ = -0.246) while CAMDA did not (-0.494). Conclusions: In this single-donor dataset, analytical design affected the estimated coupling more than the choice of summary metric. The observed range is dataset-specific and should not be interpreted as a transferable numerical estimate. Rather, these results show that evaluating plausible analytical configurations can provide important context when comparing promoter methylation summary metrics.