We present an intuitive visual framework, the generalized skyline plot, to explore the demographic history of sampled DNA sequences. This approach is based on a genealogy inferred from the sequences and provides a nonparametric estimate of effective population size through time. In contrast to previous related procedures, the generalized skyline plot is more applicable to cases where the underlying tree is not fully resolved and the data is not highly variable. This is achieved by the grouping of adjacent coalescent intervals. We employ a small-sample Akaike information criterion to objectively choose the optimal grouping strategy. We investigate the performance of our approach using simulation and subsequently apply it to HIV-1 sequences from central Africa and mtDNA sequences from red pandas.

Type

Journal article

Journal

Mol Biol Evol

Publication Date

12/2001

Volume

18

Pages

2298 - 2305

Keywords

Africa, Animals, Base Sequence, China, DNA, DNA, Mitochondrial, Data Interpretation, Statistical, Genetics, Population, HIV-1, Humans, Models, Genetic, Phylogeny, Ursidae