MFDM

MFDM detects recent positive Darwinian selection from single-locus polymorphism data using the maximum frequency of derived mutations (MFDM) statistic to assess imbalance in locus phylogenies and mitigate demographic confounding.

Key Features:

• MFDM statistic: Uses the maximum frequency of derived mutations to quantify imbalance in the phylogenetic tree at a given locus.
• Demographic independence: Provides an analytical framework that is independent from confounding demographic factors including population size fluctuations, bottlenecks, and expansions.
• High statistical power: Achieves statistical power up to 90.5% for detecting recent positive selection.
• Comparative robustness: Demonstrates resistance to confounding effects compared with Tajima's D, Fu and Li's D, Fay and Wu's H, the E test, and the joint DH test.
• Robustness to complex demography: Maintains robustness under background selection, population subdivision, admixture, and hidden population structure.
• Resilience to multiple hits: Resilient to misinference caused by multiple hits when two high-frequency mutations are present, preserving accurate derived/ancestral identification at segregating sites.
• Sensitivity to balancing selection: Sensitivity for detecting balancing selection has been explored.
• Tree-topology summary statistics: Leverages summary statistics based on tree topology and single-locus polymorphism data.

Scientific Applications:

• Detection of recent positive selection: Identifies loci under recent positive Darwinian selection from single-locus polymorphism data.
• Disentangling selection and demography: Distinguishes genetic changes driven by selection from those resulting from demographic history.
• Analyses with limited data: Applicable to studies that rely on limited DNA polymorphism or single-locus data when genome-wide data are unavailable.
• Exploration of balancing selection: Can be applied to assess sensitivity to balancing selection.

Methodology:

Computes the maximum frequency of derived mutations (MFDM) statistic from single-locus polymorphism data using tree-topology-based summary statistics; analytical derivations render the measure independent of demographic parameters, and performance was validated by simulations comparing MFDM to Tajima's D, Fu and Li's D, Fay and Wu's H, the E test, and the joint DH test.