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This 5 day course will be held at SCENE (Scottish Centre for Ecology and the Natural Environment), Glasgow, United Kingdom from August 3rd - 7th 2015 The course is being delivered by Dr. Thibaut Jombart who has contributed towards a number of R packages (adegenet, adephylo, geography, outbreaker, Outbreakertools, bmmix, episerve (author) and ade4 and phylobase (contributor) and Caitlin Collins (Imperial College London) who also contributes to the R packages adegenet, Outbreakertools and episerve) This course will provide an extensive overview of exploratory methods for the analysis of genetic data using the R software. We will address a number of key problems in population genetics, such as: How to examine genetic diversity using phylogenetic trees as well as multivariate methods, identify genetic clusters, and unravel spatial genetic patterns. Participants will be provided with the theoretical background and statistical methodology necessary to approach each problem from a number of different angles (considering, for example, univariate and multivariate approaches). Hands-on practical sessions will then provide an opportunity to highlight the pros and cons of methods introduced by the lectures, while conferring to participants advanced knowledge of the R packages adegenet, ape, and phangorn. Altogether, the aim of this course is to equip participants with powerful resources for tackling increasingly common challenges in genetic data analysis. Course timetable: Day 1: Intro to phylogenetic reconstruction Lecture 1a: Reconstructing phylogenies from genetic sequence data. Three main approaches covered: distance-based phylogenies; maximum parsimony; and likelihood-based approaches. Lecture 1b: Short R refresher. Practical 1: Phylogenetic reconstruction using R. Three main approaches plus rooting a tree; assessing/testing for a molecular clock; and bootstrapping. Main packages: ape, phangorn. Day 2: Intro to multivariate analysis of genetic data Lecture 2: Key concepts in multivariate analysis. Focus on using factorial methods for genetic data analysis. Practical 2: Basics of multivariate analysis of genetic data in R. Topics include: data handling, population genetic tests of population structure (PCA, PCoA). Main packages: adegenet, ade4, ape. Day 3: Exploring group diversity Lecture 3: Approaches to identifying and describing genetic clusters. Topics include: hierarchical clustering, K-means, population-level multivariate analysis (between-group-PCA, DA, DAPC). Practical 3: Applying the approaches covered in morning lecture and emphasising their strengths and weaknesses. Main packages: adegenet, ade4. Day 4: Genome-Wide Association Studies (GWAS) Lecture 4: Intro to GWAS study design and statistical approaches: univariate, regression-based and multivariate analysis. Practical 4: Applying each class of methods covered in morning lecture, with emphasis on their strengths and weaknesses. Main packages: adegenet, glmnet. Day 5: Spatial genetic structures Class 1: Discussing the origin and significance of spatial genetic patterns, and how to test for them. Practical: Visualising and analysing spatial genetic data. Topics: spatial density estimates, Moran/Mantel tests, mapping principal components in PCA, spatial PCA. Main packages: adegenet, adehabitat, ade4. Cost is £490 for the 5 days including lunches and refreshments or £665 for an all-inclusive option which includes the addition of accommodation, breakfast, lunch, dinner and refreshments. For further details or questions or to register please email [log in to unmask] or visit www.prstatistics.co.uk Please feel free to distribute this material among colleagues if you think it is suitable Additional upcoming courses; STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR; AN INTRODUCTION TO USING GIS IN ECOLOGICAL FIELD STUDIES; APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS; SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R; ADVANCING IN R.