Geometry of the sample frequency spectrum and the perils of demographic inference

TL;DR

This paper investigates the geometric structure of the expected sample frequency spectrum in population genetics, revealing why popular demographic inference methods often produce unstable or degenerate results due to the inherent geometry of the problem.

Contribution

It provides a geometric characterization of the expected SFS for piecewise-constant demographies and explains the intrinsic causes of pathological inference behaviors.

Findings

Expected SFS can be reconstructed with limited epochs.

Set of expected SFS is open and non-convex for fewer epochs.

Pathological inference behaviors are intrinsic to the geometry of the SFS.

Abstract

The sample frequency spectrum (SFS), which describes the distribution of mutant alleles in a sample of DNA sequences, is a widely used summary statistic in population genetics. The expected SFS has a strong dependence on the historical population demography and this property is exploited by popular statistical methods to infer complex demographic histories from DNA sequence data. Most, if not all, of these inference methods exhibit pathological behavior, however. Specifically, they often display runaway behavior in optimization, where the inferred population sizes and epoch durations can degenerate to 0 or diverge to infinity, and show undesirable sensitivity of the inferred demography to perturbations in the data. The goal of this paper is to provide theoretical insights into why such problems arise. To this end, we characterize the geometry of the expected SFS for piecewise-constant demographic histories and use our results to show that the aforementioned pathological behavior of popular inference methods is intrinsic to the geometry of the expected SFS. We provide explicit descriptions and visualizations for a toy model with sample size 4, and generalize our intuition to arbitrary sample sizes n using tools from convex and algebraic geometry. We also develop a universal characterization result which shows that the expected SFS of a sample of size n under an arbitrary population history can be recapitulated by a piecewise-constant demography with only k(n) epochs, where k(n) is between n/2 and 2n-1. The set of expected SFS for piecewise-constant demographies with fewer than k(n) epochs is open and non-convex, which causes the above phenomena for inference from data.