Introduction to Behavioral Genetics
Robbee Wedow, Felix Tropf, PhD
Date: 20.10 - 23.10.2020 ics-file
Location: Online via Zoom / Course language: English
A growing number of social science data sources are providing molecular genetic data and researchers all over the world are interested in utilizing this information in order to better understand various social phenomena. In this course, we will start with a general introduction of genetics in the social sciences. After an introduction to R and Linux computing, We will then move on to investigate issues of genetic relatedness and how heritability and genetic correlation are computed using measured genetic data with the Genomic-Relatedness-Based Restricted Maximum-Likelihood (GREML) method. After an introduction to Plink software, we will use Plink to prepare genetic data and GCTA software to estimate quantitative genetic models with the GREML method. We will also learn about the history of social science and behavior genetics as well as about the state of the art research and cutting-edge methods. We will spend time considering and learning an introduction to molecular genetics and the ethics of this field. Finally, we will discuss how genetic variants are discovered, which are associated with social science outcomes of interest and how we can utilize these results in social science research in terms of controlling for confounding effects, dealing with genetic heterogeneity in social science models, estimating gene-environment interaction models and using genes as instrumental variables. Substantively, we will rely on recently published genetic discovery studies on educational attainment, subjective well-being, same-sex sexual behavior, and fertility.
Quantitative Social Scientists, Demographers, Social Stratification Researchers, Health and Well-Being researchers.
After attending this workshop, participants should have a basic understanding of the fundamental concepts of heritability and genetic correlation. Participants will also have an understanding of how to use and manipulate genetic data in the Linux computing environment and in Plink, and will have been exposed to their first quantitative genetics models. They should also understand the basic technical terms from quantitative genetics literature and be able to read and interpret studies concerning social science genetics. They should be able to conduct basic quantitative genetics analyses and interpret their findings.
Participants need an interest and a basic understanding of quantitative social science research and basic knowledge of the software R and/or Stata.