Data from: Novel distances for Dollo data

We investigate distances on binary (presence/absence) data in the context of a Dollo process, where a trait can only arise once on a phylogenetic tree but may be lost many times. We introduce a novel distance, the Additive Dollo Distance (ADD), that applies to data generated under a Dollo model, and show that it has some useful theoretical properties including an intriguing link to the LogDet/paralinear distance. Simulations of Dollo data are used to compare a number of binary distances including ADD, LogDet, a restriction-site-based distance, and some simple, but to our knowledge previously unstudied, variations on common binary distances. The simulations suggest that ADD outperforms other distances on Dollo data. Interestingly, we found that the LogDet distance performs poorly in the context of a Dollo process, this may have implications for its use in connection with conditioned genome reconstruction. We apply the ADD to two Diversity Arrays Technology (DArT) datasets, one that broadly covers Eucalyptus species and one that focuses on the Eucalyptus series Adnataria. We also reanalyse gene family presence/absence data from bacterial genomes obtained from the COG database and compare the results to previous phylogenies estimated using the conditioned genome reconstruction approach. The results for these case studies are largely congruent with previous studies, in some cases giving more phylogenetic resolution.本研究围绕多洛演化过程（Dollo process）下的二元（存在/缺失）数据展开距离测度研究，该过程中某一性状仅可在系统发育树（phylogenetic tree）上起源一次，却可多次丢失。本研究提出一种适用于多洛模型（Dollo model）生成数据的新型距离测度——加性多洛距离（Additive Dollo Distance，ADD），并证明其具备多项实用理论性质，其中包括与LogDet/平行线性距离（LogDet/paralinear distance）存在值得关注的关联。本研究通过多洛数据模拟实验，对多种二元距离测度进行对比，涵盖ADD、LogDet、基于限制性酶切位点的距离，以及若干基于常见二元距离的简单变体——据我们所知，这类变体此前尚未被研究过。模拟实验结果表明，在多洛数据场景下，ADD的表现优于其他距离测度。值得注意的是，本研究发现LogDet距离在多洛演化过程中表现欠佳，这一结论或对其在条件基因组重建（conditioned genome reconstruction）相关应用中产生影响。本研究将ADD应用于两组多样性芯片技术（Diversity Arrays Technology，DArT）数据集：一组涵盖广泛的桉树属（Eucalyptus）物种，另一组则聚焦于桉树属Adnataria组。此外，本研究还对源自COG数据库的细菌基因组基因家族存在/缺失数据进行了重新分析，并将分析结果与此前通过条件基因组重建方法构建的系统发育树进行对比。上述案例研究的结果与既往研究大体一致，在部分案例中还实现了更高的系统发育分辨率。