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

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Authors: Angel G. Rivera-Colon, Clara T. Rehmann, Andrew D. Kern
Cited by: 2
References: 23

Abstract

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@uoregon.edu

Fields of Study & Subjects

Genetic Associations and Epidemiology Genetic and phenotypic traits in livestock Genetic diversity and population structure

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publisher
openRxiv
Publication date
4 March 2026
Language
EN
Document type
Preprint