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Context-Dependent Mutation Effects in Proteins

  • Frank J. Poelwijk
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1851)

Abstract

Defining the extent of epistasis—the nonindependence of the effects of mutations—is essential for understanding the relationship of genotype, phenotype, and fitness in biological systems. The applications cover many areas of biological research, including biochemistry, genomics, protein and systems engineering, medicine, and evolutionary biology. However, the quantitative definitions of epistasis vary among fields, and the analysis beyond just pairwise effects can be problematic. Here, we demonstrate the application of a particular mathematical formalism, the weighted Walsh-Hadamard transform, which unifies a number of different definitions of epistasis. We provide a computational implementation of such analysis using a computer-generated higher-order mutational dataset. We discuss general considerations regarding the null hypothesis for independent mutational effects, which then allows a quantitative identification of epistasis in an experimental dataset.

Key words

Epistasis Higher-order epistasis Context-dependent mutations Amino acid interactions Evolutionary biology Fitness Combinatorial mutagenesis 

Notes

Acknowledgments

I thank Michael A. Stiffler and DerZen Fan for critical reading of the manuscript.

Supplementary material

426856_1_En_7_MOESM1_ESM.zip (22 kb)
Data 1 Computational Scripts in MATLAB (ZIP 23 KB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Frank J. Poelwijk
    • 1
  1. 1.cBio Center, Department of Biostatistics and Computational BiologyDana-FarberCancer InstituteBostonUSA

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