Exploring the demographic history of DNA sequences using the generalized skyline plot

K Strimmer, OG Pybus

    Research output: Contribution to journalArticlepeer-review

    Abstract

    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.
    Original languageEnglish
    Pages (from-to)2298-2305
    JournalMolecular Biology and Evolution
    Volume18
    Issue number12
    DOIs
    Publication statusPublished - Dec 2001

    Keywords

    • coalescent process
    • corrected Akaike criterion
    • HIV-1 model selection
    • likelihood
    • red panda
    • skyline plot

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