MKado: a toolkit for McDonald-Kreitman tests of natural selection

Abstract Summary MKado is a Python toolkit for performing McDonald-Kreitman (MK) tests of natural selection from aligned coding sequences. It implements the standard MK test as well as a wide variety of its extensions and related statistics, including a number of methods for estimating the fraction of adaptive substitutions (α) while accounting for slightly deleterious mutations, with a unified command-line interface and Python API. MKado supports parallel batch processing of thousands of genes with near-linear scaling, and provides publication-ready visualizations including volcano plots and asymptotic α curves. Availability and Implementation MKado is freely available at https://github.com/kr-colab/mkado under the MIT license. Full documentation is available at https://mkado.readthedocs.io. MKado is implemented in Python and installable via pip. Contact adkern{at}uoregon.edu Competing Interest Statement The authors have declared no competing interest. Footnotes minor changes to accompany revisions including new features in the software and a new analysis