Munch Kasper, Boomsma Wouter, Huelsenbeck John P, Willerslev Eske, Nielsen Rasmus
Department of Integrative Biology, University of California, Berkeley, California 94720-3140, USA.
Syst Biol. 2008 Oct;57(5):750-7. doi: 10.1080/10635150802422316.
We provide a new automated statistical method for DNA barcoding based on a Bayesian phylogenetic analysis. The method is based on automated database sequence retrieval, alignment, and phylogenetic analysis using a custom-built program for Bayesian phylogenetic analysis. We show on real data that the method outperforms Blast searches as a measure of confidence and can help eliminate 80% of all false assignment based on best Blast hit. However, the most important advance of the method is that it provides statistically meaningful measures of confidence. We apply the method to a re-analysis of previously published ancient DNA data and show that, with high statistical confidence, most of the published sequences are in fact of Neanderthal origin. However, there are several cases of chimeric sequences that are comprised of a combination of both Neanderthal and modern human DNA.
我们基于贝叶斯系统发育分析提供了一种用于DNA条形码的新型自动化统计方法。该方法基于使用自定义构建的贝叶斯系统发育分析程序进行自动化数据库序列检索、比对和系统发育分析。我们通过实际数据表明,作为一种置信度衡量方法,该方法优于Blast搜索,并且可以帮助消除基于最佳Blast比对结果的所有错误分类中的80%。然而,该方法最重要的进展在于它提供了具有统计学意义的置信度衡量指标。我们将该方法应用于对先前发表的古代DNA数据的重新分析,结果表明,在具有高度统计置信度的情况下,大多数已发表序列实际上起源于尼安德特人。然而,存在几例嵌合序列,它们由尼安德特人和现代人类DNA的组合构成。