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Quantitative Genetics Workshop

Innovation Lab for Crop Improvement – QuickWin Project
📚 Workshop Website


🎯 Workshop Overview

This workshop introduces fundamental concepts in quantitative genetics with applications in genomic selection and breeding. It is part of the Innovation Lab for Crop Improvement’s QuickWin project.

Participants will gain theoretical knowledge and practical skills for analyzing genetic data using R, with an emphasis on genomic prediction.


🧠 Learning Objectives

By the end of this workshop, participants will be able to:

  • Understand the basic principles of quantitative inheritance.
  • Describe the genetic and environmental components of phenotypic variance.
  • Apply linear models to estimate genetic effects.
  • Understand and implement basic concepts of genomic selection.

📚 Course Materials

The workshop draws from the following textbooks:

  • Introduction to Quantitative Genetics (4th Edition) by Falconer & Mackay
  • Breeding for Quantitative Traits in Plants (3rd Edition) by Bernardo
  • Introduction to Genetic Analysis (10th Edition) by Griffiths, Wessler, Carroll & Doebley

Additional materials (lecture slides, videos, and R code) are available at:
👉 https://pauloizquierdo.github.io/QuantitativeGenetics/


🧑‍🏫 Workshop Format

  • 9 pre-recorded lectures (20–30 minutes each), released via the website
  • 3 live discussion sessions (1 hour each), covering 3 lectures per session

💬 Engagement

To foster interactive discussion:

  • Participants are encouraged to submit at least one question per discussion session.
  • Questions can be based on lecture content or related papers.

🛠 Requirements

  • R (≥ 4.0.0)
  • R packages used in examples will be listed on the workshop website
  • Internet connection to access video content and materials

✍️ License

Materials shared in this repository are intended for educational use. Please credit the authors and workshop organizers when using or adapting them.


🙌 Acknowledgments

This workshop is supported by the Innovation Lab for Crop Improvement (ILCI) under the QuickWin Project.


For questions or contributions, please contact the workshop instructor via the website.

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