Speed‐ne: Software to simulate and estimate genetic effective population size (Ne) from linkage disequilibrium observed in single samples

Abstract

The genetic effective population size, Ne , can be estimated from the average gametic disequilibrium (r2^) between pairs of loci, but such estimates require evaluation of assumptions and currently have few methods to estimate confidence intervals. speed-ne is a suite of matlab computer code functions to estimate Ne^ from r2^ with a graphical user interface and a rich set of outputs that aid in understanding data patterns and comparing multiple estimators. speed-ne includes functions to either generate or input simulated genotype data to facilitate comparative studies of Ne^ estimators under various population genetic scenarios. speed-ne was validated with data simulated under both time-forward and time-backward coalescent models of genetic drift. Three classes of estimators were compared with simulated data to examine several general questions: what are the impacts of microsatellite null alleles on Ne^, how should missing data be treated, and does disequilibrium contributed by reduced recombination among some loci in a sample impact Ne^. Estimators differed greatly in precision in the scenarios examined, and a widely employed Ne^ estimator exhibited the largest variances among replicate data sets. speed-ne implements several jackknife approaches to estimate confidence intervals, and simulated data showed that jackknifing over loci and jackknifing over individuals provided ~95% confidence interval coverage for some estimators and should be useful for empirical studies. speed-ne provides an open-source extensible tool for estimation of Ne^ from empirical genotype data and to conduct simulations of both microsatellite and single nucleotide polymorphism (SNP) data types to develop expectations and to compare Ne^ estimators.