Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
Department of Biology, Temple University, Philadelphia, PA, USA.
Mol Biol Evol. 2023 Jul 5;40(7). doi: 10.1093/molbev/msad165.
Repeated runs of the same program can generate different molecular phylogenies from identical data sets under the same analytical conditions. This lack of reproducibility of inferred phylogenies casts a long shadow on downstream research employing these phylogenies in areas such as comparative genomics, systematics, and functional biology. We have assessed the relative accuracies and log-likelihoods of alternative phylogenies generated for computer-simulated and empirical data sets. Our findings indicate that these alternative phylogenies reconstruct evolutionary relationships with comparable accuracy. They also have similar log-likelihoods that are not inferior to the log-likelihoods of the true tree. We determined that the direct relationship between irreproducibility and inaccuracy is due to their common dependence on the amount of phylogenetic information in the data. While computational reproducibility can be enhanced through more extensive heuristic searches for the maximum likelihood tree, this does not lead to higher accuracy. We conclude that computational irreproducibility plays a minor role in molecular phylogenetics.
在相同的分析条件下，同一数据集的同一程序重复运行可能会生成不同的分子系统发育树。这种推断系统发育树的不可重复性给下游研究带来了很大的影响，这些下游研究在比较基因组学、系统学和功能生物学等领域中使用了这些系统发育树。我们评估了替代系统发育树在计算机模拟和经验数据集上的相对准确性和对数似然值。我们的研究结果表明，这些替代系统发育树以相似的准确性重建了进化关系。它们的对数似然值也不低于真实树的对数似然值。我们确定不可重复性和不准确性之间的直接关系是由于它们共同依赖于数据中的系统发育信息量。虽然通过更广泛的启发式搜索来寻找最大似然树可以提高计算的可重复性，但这并不会导致更高的准确性。我们得出结论，计算不可重复性在分子系统发育学中只起次要作用。
