Genomic Selection

Genomic Selection


1-4 September 2020
The aim of this course is to provide a basic quantitative and statistical framework to apply GS in a routine manner. In this sense, the course is focusing on the application of plant breeding concepts through practical exercises in R.

The course will provide participants with the relevant theory of GS models, as well as with hands-on experience with relevant GS techniques
  • To have the fundamental knowledge to build GS models from the scratch.
  • To have a basic understanding of the main statistical concepts of GS methods.
  • To learn how to apply GxE models, Multi-trait analysis and Hybrid prediction.
  • To learn about optimal parental contributions and mating designs for multi-criteria breeding.
  • The course is aimed at plant breeder scientists, graduate students, postdocs and professionals in the field of plant-crop production who are interested to learn concepts in a problem-based learning approach.

    Although, the course is not aimed at researchers with advanced statistical skills. Participants should be familiar with plant breeding and statistical concepts. Course tutorials will use statistical packages in R, and experience is R is recommended but is not essential.

    A certificate of attendance will be provided at the end of the course. This course will be equivalent to 2.5 credits. For those participants who wish to obtain a certificate of attendance of the equivalence of 2.5 credit module, a series of reading and exercises will be provided before, during and after the course to assure the student achieves the learning outcomes.


    Class notes will be distributed during the course, and a Dropbox/Google drive folder will be used to share R code, lectures and exercises. Please bring your personal. R and Rstudio should be installed in your computer to run the analysis.


    The tentative main hub for the course will be the Cabildo of Lanzarote ́s within the Public Library If you want to visit Lanzarote, check this video


    Participants are responsible for their own accommodation. There are many hotel options in the area, this is an example Airbnb is a great option too.


    For further information do not hesitate to contact me.
    Day 1 Day 2 Day 3 Day 4
    Quantitative Genetics/R programming/ Linear models

    We will focus on quantitative genetics, especially on:
  • Review of Quantitative genetics/ Quantitative trait loci
  • Sources of quantitative trait variation
  • Breeding Values and Heritabilities
  • Response from selection
  • Resemblance among relatives
  • Big Picture of Genomic selection/ Machine learning approach
  • Linear Models/ANOVA/GLM
  • Genomic Selection in R
  • Factors affecting Genomic Selection
  • Optimization of GS
  • Fixed-Random Effects
  • Best Linear Unbiased Estimator
  • Best Linear Unbiased Predictor
  • Statistical concepts for Genomic Selection analysis in R
  • Pedigree vs. Kinship matrix
  • Imputation
  • Statistical Models
  • Genotype X Environment interaction
  • Multi-trait analysis
  • Hybrid prediction
  • Statistical Analysis in Genomic Selection: Genomic Mating
  • One-step model
  • Two-Step models
  • Cross-Validations
  • Parental proportion and genomic mating
  • Instructors

    Dr. Julio Isidro Sánchez
    University College Dublin + info
    Genomic Selection
    Dr. Deniz Akdemir
    University College Dublin + info
    Genomic Selection


    Please note the deadline for registering to this programme is 20 July 2020.

    These fees include, morning and afternoon breaks and one group dinner. Accommodations are not included. Scholarships or reduced fees are unavailable.


    € 899


    € 499