Genomic Prediction of Complex Traits (GPCT01) – Applications for Marine Mammal Research
Genomic Prediction of Complex Traits (GPCT01)<https://prstats.org/course/genomic-prediction-of-complex-traits-gpct01/?utm_source=chatgpt.com> Delivered by Dr. Javier Fernández-González, a quantitative geneticist and biostatistician specialising in statistical genomics, quantitative genetics, genomic prediction, variance-component estimation, and the statistical analysis of complex traits. Learn how to use genome-wide genetic and phenotypic data to analyse and predict complex traits, with approaches applicable to marine mammal population biology, conservation genomics, evolutionary ecology, and studies of genotype–environment relationships. Many traits of interest in marine mammal research — including morphology, body size, reproductive performance, physiology, disease susceptibility, behaviour, and responses to environmental conditions — are complex quantitative traits influenced by many genetic variants together with environmental effects. Genomic prediction provides a framework for investigating this complexity by combining genome-wide marker and phenotypic information to estimate genetic effects, quantify heritability, predict complex phenotypes, and explore genetic and environmental contributions to biological variation. What you'll gain * An understanding of the fundamental principles of genomic prediction and genomic selection * Insight into factors influencing genomic prediction accuracy * A practical understanding of linear models, fixed and random effects, covariance structures, REML, and shrinkage * Experience with genomic prediction models including GBLUP and rrBLUP * Skills constructing and interpreting genomic relationship matrices * Methods for estimating heritability * Approaches for estimating additive and non-additive genetic effects * Understanding of single-stage and multi-stage modelling * Introduction to Bayesian and machine-learning alternatives * Practical experience preparing phenotypic and genotypic data * Understanding of cross-validation for evaluating predictive performance * Introduction to multi-trait genomic prediction * Approaches for modelling genotype-by-environment interactions Course format * 5-day live, instructor-led online course * 22.5 hours of training * Combination of lectures and hands-on practical exercises * Practical implementation using realistic genomic datasets * Opportunity to discuss participants' own data * All code, datasets, and presentation materials provided * All sessions recorded * 30 days of recording access and post-course email support Who is this course for? * Marine mammal researchers working with genetic or genomic data * Cetacean and pinniped researchers * Marine evolutionary and molecular ecologists * Conservation geneticists and genomic researchers * Population and quantitative geneticists * Researchers studying complex biological traits * Researchers investigating genotype-by-environment interactions * Researchers combining genomic, phenotypic, and environmental data * Postgraduate students and early-career researchers Participants should have a basic understanding of quantitative and population genetics, molecular biology, statistics, and matrix algebra, together with some familiarity with R. Why take this course? Genomic approaches are increasingly used in marine mammal research to understand genetic variation, phenotypic differences, adaptation, population biology, and responses to changing environmental conditions. Many biologically important characteristics are polygenic, making approaches that consider genome-wide variation particularly valuable. Genomic prediction provides tools for examining these complex traits by using information distributed across the genome. The methods taught in this course allow researchers to estimate heritability, model genomic relationships, quantify additive and non-additive genetic effects, and predict complex phenotypes. Of particular relevance to marine mammal and conservation research is the course's introduction to genotype-by-environment interactions. These models provide a framework for investigating how genetic effects may differ across environmental conditions — potentially valuable when studying populations exposed to different habitats, climates, prey availability, pollutants, or other environmental pressures. The course also introduces multi-trait prediction and Bayesian and machine-learning alternatives to conventional linear mixed models. Whether you're investigating complex traits, adaptation, phenotypic variation, environmental responses, conservation genomics, or genotype–environment interactions in cetaceans, pinnipeds, or other marine mammals, this course provides a practical introduction to genomic prediction methods that can be incorporated into marine mammal research. Course dates 21–25 September 2026 22.5 hours | Live online | £400 Learn more & enrol PR Stats – Genomic Prediction of Complex Traits (GPCT01)<https://prstats.org/course/genomic-prediction-of-complex-traits-gpct01/?utm_source=chatgpt.com> Questions? 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