Neutral and Stable Equilibria of Genetic Systems and The Hardy-Weinberg Principle: Limitations of the Chi-Square Test and Advantages of Auto-Correlation Functions of Allele Frequencies
Francisco Bosco, Diogo Castro, Marcelo R. S. Briones

TL;DR
This paper challenges the traditional use of the Hardy-Weinberg principle and Chi-Square tests in population genetics, proposing that allele frequency auto-correlation functions provide a better understanding of genetic dynamics and equilibrium.
Contribution
It demonstrates the limitations of Chi-Square tests for Hardy-Weinberg equilibrium and introduces auto-correlation functions as a more effective tool for analyzing genetic stability.
Findings
Chi-Square tests can give false positives and negatives in population analysis.
Under Hardy-Weinberg conditions, populations evolve neutrally and do not reach observable equilibrium.
Relaxing random mating leads to asymptotic stable equilibrium characteristics.
Abstract
Since the foundations of Population Genetics the notion of genetic equilibrium (in close analogy to Classical Mechanics) has been associated to the Hardy-Weinberg (HW) Principle and the identification of equilibrium is currently assumed by stating that the HW axioms are valid if appropriate values of Chi-Square (p<0.05) are observed in experiments. Here we show by numerical experiments with the genetic system of one locus/two alleles that considering large ensembles of populations the Chi-Square test is not decisive and may lead to false negatives in random mating populations and false positives in nonrandom mating populations. As a result we confirm the logical statement that statistical tests can not be used to deduce if the genetic population is under the HW conditions. Furthermore, we show that under the HW conditions populations of any finite size evolve in time according to what…
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