One of the most widely used programs for detecting positive selection, at the molecular level, is the program codeml, which is implemented in the Phylogenetic Analysis by Maximum Likelihood (PAML) package. However, it has a limitation when it comes to genome-wide studies, as it runs on a gene-by-gene basis. Furthermore, the size of such studies will depend on the number of orthologous genes the genomes have income and these are often restricted to only account for instances where a one-to-one relationship is observed between the genomes. In this work, we present GWideCodeML, a Python package, which runs a genome-wide codeml with the option of parallelization. To maximize the number of analyzed genes, the package allows for a variable number of taxa in the alignments and will automatically prune the topology to fit each of them, before running codeml.

在分子水平上用于检测阳性选择的最广泛使用的程序之一是程序ml，该程序在“通过最大可能性的系统发育分析”（PAML）程序包中实现。但是，它在全基因组研究中存在局限性，因为它是逐个基因地运行。此外，此类研究的规模将取决于基因组具有收益的直系同源基因的数量，而这些通常被限制为仅考虑在基因组之间观察到一对一关系的情况。在这项工作中，我们展示了GWideCodeML，这是一个Python软件包，可运行全基因组密码与并行化选项。为了最大化分析基因的数量，该程序包允许在比对中使用不同数量的分类单元，并在运行codeml之前自动修剪拓扑以适合每个基因组。