LDscnR: LD-aware complexity reduction for genome scans

LDscnR, using chromosome-specific LD-decay thresholds, groups correlated markers into phenotype-blind units and reports outlier regions, cutting tests by 80% in high gene-flow simulations.

• Why it matters: Marker-wise genome scans can inflate candidate counts and overstate multiple-testing burden, while structure alone can generate apparent outlier regions that are hard to disentangle.
• What they did: LDscnR calibrates clustering to LD decay, tests each eligible unit once, and merges nearby significant units into regions; it also builds nulls from spatially structured surrogate phenotypes.
• The result: In high gene-flow simulations, region-level precision rose by more than 50% with <12% recall loss, and stickleback analyses found 39 LDscnR outlier regions vs 19 SNPs by marker-wise EMMAX.