The availability of genome-wide data provides unprecedented opportunities for resolving difficult phylogenetic relationships and for studying population genetic processes of mutation, selection, and recombination on a genomic scale. The use of appropriate statistical models becomes increasingly important when we are faced with very large datasets, which can lead to improved precision but not necessarily improved accuracy if the analytical methods have systematic biases. This review provides a critical examination of methods for analyzing genomic datasets from multiple loci, including concatenation, separate gene-by-gene analyses, and statistical models that accommodate heterogeneity in different aspects of the evolutionary process among data partitions. We discuss factors that may cause the gene tree to differ from the species tree, as well as strategies for estimating species phylogenies in the presence of gene tree conflicts. Genomic datasets provide computational and statistical challenges that are likely to be a focus of research for years to come.

中文翻译：

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使用整个基因组进行系统发育推断。

全基因组数据的可用性为解决困难的系统发育关系以及研究基因组规模的突变，选择和重组的群体遗传过程提供了前所未有的机会。当我们面对非常大的数据集时，使用适当的统计模型变得越来越重要，这可能会导致精度提高，但如果分析方法具有系统性偏差，则不一定会提高精度。这篇综述提供了对分析来自多个基因座的基因组数据集的方法的批判性检查，包括级联，单独的逐个基因分析以及统计模型，这些模型可适应数据分区之间进化过程不同方面的异质性。我们讨论了可能导致基因树与物种树不同的因素，以及在存在基因树冲突的情况下估算物种系统发育的策略。基因组数据集提供了计算和统计方面的挑战，这可能是未来几年研究的重点。