RT Journal Article
SR Electronic
T1 Flexible methods for estimating genetic distances from nucleotide data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 004184
DO 10.1101/004184
A1 Simon Joly
A1 David Bryant
A1 Peter J. Lockhart
YR 2014
UL http://biorxiv.org/content/early/2014/04/12/004184.abstract
AB 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) if they can accurately identify the genomic mixture of hybrid individuals and (iii) if they give precise (low variance) estimates.The results showed that the SNP-based GENPOFAD distance we propose appears to work well in the widest circumstances. It was the most accurate 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 distance measures in specific situations.