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Missing Data and Influential Sites: Choice of Sites for Phylogenetic Analysis Can Be As Important As Taxon Sampling and Model Choice

机译:数据丢失和有影响的位点:系统发生分析的位点选择与分类群采样和模型选择同等重要

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摘要

Phylogenetic studies based on molecular sequence alignments are expected to become more accurate as the number of sites in the alignments increases. With the advent of genomic-scale data, where alignments have very large numbers of sites, bootstrap values close to 100% and posterior probabilities close to 1 are the norm, suggesting that the number of sites is now seldom a limiting factor on phylogenetic accuracy. This provokes the question, should we be fussy about the sites we choose to include in a genomic-scale phylogenetic analysis? If some sites contain missing data, ambiguous character states, or gaps, then why not just throw them away before conducting the phylogenetic analysis? Indeed, this is exactly the approach taken in many phylogenetic studies. Here, we present an example where the decision on how to treat sites with missing data is of equal importance to decisions on taxon sampling and model choice, and we introduce a graphical method for illustrating this.
机译:随着比对中位点数目的增加,基于分子序列比对的系统发生研究有望变得更加准确。随着基因组规模数据的到来,其中比对具有非常多的位点,自举值接近100%,后验概率接近1,这表明位点数现在已经很少成为限制系统发育准确性的限制因素。这就引发了一个问题,我们是否应该对我们选择纳入基因组规模的系统发育分析的位点大做文章?如果某些站点包含丢失的数据,模棱两可的字符状态或空白,那么为什么不进行系统发育分析之前就把它们扔掉呢?确实,这正是许多系统发育研究中采用的方法。在这里,我们提供一个示例,其中如何处理缺少数据的站点的决定与分类单元采样和模型选择的决定同等重要,并且我们引入了一种图形方法来说明这一点。

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