**From the organisers**
Currently, the University of Oxford is closed due to the COVID-19 pandemic.
The situation with COVID-19 is changing quickly. In light of this uncertainty, after considering various options, we regret to report that we have decided to postpone the summer school.
As things develop over the next few weeks and months we will reassess the situation and decide how to move forward. We appreciate your understanding and flexibility during this time.
We wanted to inform you as soon as possible since some of you may be making travel plans or still planning this into your schedules.
Once we know more about this situation, we can decide if and when we can hold it later this year. Or, in the event that it remains very uncertain, we can transfer your admission to next year’s course.
Sincerely,
The OGSX4 Organisers
The Oxford Genomics for Social Scientists Summer School is offered jointly this year in collaboration with the University of Michigan, National Institute of Aging parallel summer school. This course offers an introduction to familiarize researchers interested in incorporating genetic information into their analyses.
This one-week course is aimed at providing introductory lectures by top scholars in the field of sociogenomics including Dalton Conley (Princeton), Melinda Mills (Oxford), biology and genetics Molly Przeworski (Columbia), lead researchers on key datasets (David Weir, Health and Retirement Survey) but also hands-on computer lab training by experts in the field including Andrew Grotzinger on Genomic SEM, Nicola Barban, Felix Tropf, David Brazel and Xuejie Ding.
The course will equip students with a unique insight into the emerging topic of sociogenomics and the most cutting-edge methodological techniques in this area of research. The focus will be on understanding the key substantive research questions in this area, an overview of data that is increasingly available, hands-on computer lesson of how to work with genetic data, and an introduction into the current methodological techniques used in the field.
The course is aimed at graduate students and early career researchers interested in engaging in research on this topic. It is designed to primarily benefit those who have some experience in statistical analyses but little or no biological or genetic training. Working with world-class researchers and instructors, you will have the opportunity to gain new skills in this emerging field.
Morning lectures will focus on substantive examples of topics in this field including: a primer on fundamental concepts and the human genome, statistical models for genetic data analysis, human evolution, genome-wide association studies, polygenic scores and gene-environment interplay. Throughout we will use examples often studied by social scientists such as education, reproductive behaviour, well-being, externalizing behaviour, addiction and risk. Students will also learn about genetic data and analytical challenges.
Afternoon lectures will consist of hands-on computer labs covering how to navigate genetic data files (data management, quality control), key calculations (e.g., association analysis, genetic relatedness) and creating and applying polygenic scores. Lectures will also include various polygenic score and gene-environment interaction applications.
Students who are accepted will receive a general reading list in advance, which includes the new introductory textbook An Introduction to Statistical Genetic Data Analysis (Mills, Barban, Tropf, 2020).
The expectation is that students will have basic skills in the statistical programme R. Students who do not have these skills are still encouraged to apply, but then invited to follow an on-line pre-course tutorial.
Register by February 15, 2020.