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G3 (Bethesda). 2017 May 5;7(5):1569-1575. doi: 10.1534/g3.117.039693.

asymptoticMK: A Web-Based Tool for the Asymptotic McDonald-Kreitman Test.

Author information

1
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853.
2
Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14853 messer@cornell.edu.

Abstract

The McDonald-Kreitman (MK) test is a widely used method for quantifying the role of positive selection in molecular evolution. One key shortcoming of this test lies in its sensitivity to the presence of slightly deleterious mutations, which can severely bias its estimates. An asymptotic version of the MK test was recently introduced that addresses this problem by evaluating polymorphism levels for different mutation frequencies separately, and then extrapolating a function fitted to that data. Here, we present asymptoticMK, a web-based implementation of this asymptotic MK test. Our web service provides a simple R-based interface into which the user can upload the required data (polymorphism and divergence data for the genomic test region and a neutrally evolving reference region). The web service then analyzes the data and provides plots of the test results. This service is free to use, open-source, and available at http://benhaller.com/messerlab/asymptoticMK.html We provide results from simulations to illustrate the performance and robustness of the asymptoticMK test under a wide range of model parameters.

KEYWORDS:

molecular evolution; positive selection; web service

PMID:
28341700
PMCID:
PMC5427504
DOI:
10.1534/g3.117.039693
[Indexed for MEDLINE]
Free PMC Article

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