Statistical Properties of New Neutrality Tests Against Population Growth

TLDR

Statistical tests for detecting population growth are described. The study compares the statistical power of these tests with other available tests. The tests evaluated are grouped into three categories: mutation‑frequency, haplotype, and mismatch‑distribution based methods. Fu's FS and the new R2 test are the most powerful for detecting population growth, with R2 outperforming for small samples and FS for large samples, while mismatch‑distribution statistics are generally conservative.

Abstract

A number of statistical tests for detecting population growth are described. We compared the statistical power of these tests with that of others available in the literature. The tests evaluated fall into three categories: those tests based on the distribution of the mutation frequencies, on the haplotype distribution, and on the mismatch distribution. We found that, for an extensive variety of cases, the most powerful tests for detecting population growth are Fu's FS test and the newly developed R2 test. The behavior of the R2 test is superior for small sample sizes, whereas FS is better for large sample sizes. We also show that some popular statistics based on the mismatch distribution are very conservative.