Statistics – Applications
Scientific paper
2009-06-05
Annals of Applied Statistics 2009, Vol. 3, No. 1, 222-248
Statistics
Applications
Published in at http://dx.doi.org/10.1214/08-AOAS212 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Ins
Scientific paper
10.1214/08-AOAS212
The amplified fragment length polymorphism (AFLP) method produces anonymous genetic markers from throughout a genome. We extend the nucleotide substitution model of AFLP evolution to additionally include insertion and deletion processes. The new Sub-ID model relaxes the common assumption that markers are independent and homologous. We build a Markov chain Monte Carlo methodology tailored for the Sub-ID model to implement a Bayesian approach to infer AFLP marker evolution. The method allows us to infer both the phylogenies and the subset of markers that are possibly homologous. In addition, we can infer the genome-wide relative rate of indels versus substitutions. In a case study with AFLP markers from sedges, a grass-like plant common in North America, we find that accounting for insertion and deletion makes a difference in phylogenetic inference. The inference of topologies is not sensitive to the prior settings and the Jukes--Cantor assumption for nucleotide substitution. The model for insertion and deletion we introduce has potential value in other phylogenetic applications.
Larget Bret
Luo Ruiyan
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