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Flexible methods for estimating genetic distances from nucleotide data

By Simon Joly, David Bryant, Peter J Lockhart

Posted 14 Apr 2014
bioRxiv DOI: 10.1101/004184 (published DOI: 10.1111/2041-210X.12343)

With the increasing use of massively parallel sequencing approaches in evolutionary biology, the need for fast and accurate methods suitable to investigate genetic structure and evolutionary history are more important than ever. We propose new distance measures for estimating genetic distances between individuals when allelic variation, gene dosage and recombination could compromise standard approaches. We present four distance measures based on single nucleotide polymorphisms (SNP) and evaluate them against previously published measures using coalescent- based simulations. Simulations were used to test (i) whether the measures give unbiased and accurate distance estimates, (ii) whether they can accurately identify the genomic mixture of hybrid individuals and (iii) whether they give precise (low variance) estimates. The effect of rate variation among genes and recombination was also investigated. The results showed that the SNP-based GENPOFAD distance we propose appears to work well in the widest range of circumstances. It was the most accurate and precise method for estimating genetic distances and is also relatively good at estimating the genomic mixture of hybrid individuals. Our simulations provide benchmarks to compare the performance of different method that estimate genetic distances between organisms.

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