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Coding Genetics

Simulating and analyzing population genetics with R

Jacob C. Koella

Modern genetics increasingly relies on mathematical models and computational tools. Coding Genetics guides you through the core concepts of population genetics, from the dynamics of allele frequencies to the analysis of genomic data, and shows how to implement and explore these ideas by building models in R.

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About the Book

The genomics revolution has transformed biology into a quantitative science, making mathematical models and computer programming essential for understanding genetic processes. Coding Genetics provides a clear, hands-on introduction to population genetics, from the forces that shape allele frequencies to the analysis of real genetic data. Using R throughout, the book shows how to build, explore, and visualise models of evolutionary change, enabling readers to move beyond formulas to genuine understanding. It is written for students and researchers who want to see how genetic theory works in practice, and how to implement it themselves.

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RBiology

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About the Author

Jacob C. Koella

Jacob Koella is a professor of evolutionary biology and parasitology at the [University of Neuchâtel] (https://www2.unine.ch) in Switzerland. 

With the equivalent of Masters' degree in mechanical engineering (with an emphasis on systems dynamics), a Phd in evolutionary ecology and several years experience in the epidemiology of malaria, he conducts a considerable part of his research on mathematical theory combining the epidemiology and evolutionary ecology of parasites.

He teaches courses on mathematical modelling, parasitology and evolutionary ecology at the University of Neuchâtel and at the ETH Zurich.

Contents

Table of Contents

Introduction

Essentials of R

  1. Installing R and an R interface
  2. Getting started: R as a calculator
  3. What if we want to store the results of our calculations?
  4. Object types
  5. Vectors
  6. Matrices
  7. Data frames
  8. Control structures
  9. Functions
  10. Simple plots

Dynamics of population genetics

  1. An example: sickle cell anaemia
  2. Hardy-Weinberg equilibrium: a null model for population genetics
  3. Genetic drift
  4. Non-random mating
  5. Selection
  6. Two-locus genetics

Analysis of genetic patterns

  1. Allele frequencies
  2. Hardy-Weinberg
  3. Spatial structure and genetic drift
  4. Signature of selection
  5. Genomic relationships
  6. Summary

Exercises

  1. Essentials of R
  2. Dynamics of genes
  3. Analysis of genetic patterns

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