Training on methodology for biology-driven selection
The training on methodology for biology-driven selection was held on 25th – 28th of September 2023, at the University of Aarhus, Denmark.
Contact: emre@qgg.au.dk or terhi.iso-touru@luke.fi
List of available presentations:
- Aniek Bouwman (WUR) – Biology-driven genomic predictions for dry matter intake within and across breeds using WGS data
- Zexi Cai (AU) – Variants annotation using VEP
- Ole F. Christensen (AU) – Incorporating high-dimensional omics phenotypes into models for predicting breeding values
- Ole F. Christensen (AU) – Best linear unbiased prediction (animal model)
- Ole F. Christensen (AU) – Variances, covariances, matrices, genetic relationships
- Ole F. Christensen (AU) – Genomic models and BLUP
- Praveen Chitneedi (FBN) – eQTL/sQTLdetection using Nextflow-based workflow
- Beatriz Castro-Dias-Cuyabano (INRAE) – Bayesian methods applied to genomic prediction and genome-wide association studies (GWAS)
- Ismo Strandén (LUKE) – Inclusion of functional annotations into single-step genomic prediction
For complementary material used for practicals, please contact liguori@eaap.org
Program:
| Day | Morning | Afternoon |
| 1 – (25 Sep) | – Overview of BovReg project.
– Shared experience with real data – Introduction to eQTL detection using Nextflow based workflow – Live demo of the analysis by downloading the workflow from GitHub – The complexity of eukaryotic genome – Hands-on practice for variants annotation. |
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| 2 – (26 Sep) | – Repetition of matrices, variances and covariances, animal model, BLUP, GBLUP, MBLUP | – Introduction to Bayesian Statistics
– Bayesian methods in GS: BayesA, BayesB, BayesC, and RKHS Bayes |
| 3 – (27 Sep) | – Practical session with exercises to apply and compare Bayesian methods on a small data set | – Whole genome regression methods for including functional annotations
– Introduction to NextGP.jl package for “omics” data analysis |
| 4 – (28 Sep) | – Biology informed genomic predictions
– Inclusion of functional annotations into single-step genomic prediction |