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Identifying localized biases in large datasets: A case study using the avian tree of life

机译:识别大型数据集中的局部偏差:使用鸟类生命之树的案例研究

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Large-scale multi-locus studies have become common in molecular phylogenetics, with new studies continually adding to previous datasets in an effort to fully resolve the tree of life. Total evidence analyses that combine existing data with newly collected data are expected to increase the power of phylogenetic analyses to resolve difficult relationships. However, they might be subject to localized biases, with one or a few loci having a strong and potentially misleading influence upon the results. To examine this possibility we combined a newly collected 31-locus dataset that includes representatives of all major avian lineages with a published dataset of 19 loci that has a comparable number of sites (Hackett et al., 2008. Science 320, 1763-1768). This allowed us to explore the advantages of conducting total evidence analyses, and to determine whether it was also important to analyze new datasets independent of published ones. The total evidence analysis yielded results very similar to the published results, with only slightly increased support at a few nodes. However, analyzing the 31- and 19-locus datasets separately highlighted several differences. Two clades received strong support in the published dataset and total evidence analysis, but the support appeared to reflect bias at a single locus (β-fibrinogen [FGB]). The signal in FGB that supported these relationships was sufficient to result in their recovery with bootstrap support, even when combined with 49 loci lacking that signal. FGB did not appear to have a substantial impact upon the results of species tree methods, but another locus (brain-derived neurotrophic factor [BDNF]) did have an impact upon those analyses. These results demonstrated that localized biases can influence large-scale phylogenetic analyses but they also indicated that considering independent evidence and exploring multiple analytical approaches could reveal them.
机译:大规模的多基因座研究已在分子系统发育学中变得很普遍,而新的研究不断地添加到以前的数据集中,以努力完全解决生命之树。将现有数据与新收集的数据相结合的全面证据分析有望提高系统发育分析解决困难关系的能力。但是,它们可能会受到局部偏差的影响,一个或几个基因座会对结果产生强烈且可能具有误导性的影响。为了检验这种可能性,我们将一个包括所有主要禽类谱系代表的新收集的31位基因组数据与一个已公布的19个基因座的数据集相结合,该基因座具有相当数量的位点(Hackett et al。,2008. Science 320,1763-1768)。 。这使我们能够探索进行全面证据分析的优势,并确定分析独立于已发布数据集的新数据集是否也很重要。总体证据分析得出的结果与已发布的结果非常相似,只是在几个节点上的支持略有增加。但是,分别分析31和19位基因组的数据集会突出显示出一些差异。在公布的数据集和全面证据分析中,两个进化枝获得了强有力的支持,但这种支持似乎反映了单个基因座(β-纤维蛋白原[FGB])的偏倚。 FGB中支持这些关系的信号足以通过引导程序支持来恢复它们,即使与缺少该信号的49个基因座结合使用也是如此。 FGB似乎对物种树方法的结果没有实质性影响,但是另一个基因座(脑源性神经营养因子[BDNF])确实对那些分析有影响。这些结果表明,局部偏见可以影响大规模的系统发育分析,但同时也表明,考虑独立证据并探索多种分析方法可以揭示这些现象。

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