## Breadcrumb

## Theory & background

### All

#### A1. Introduction to the Unix/Linux command line

Jeffrey Lessem, June 2021 Virtual Workshop

A brief introduction to using the Unix/Linux command line focusing on tasks that will be necessary for practicals at the Workshop. It covers basic concepts that people who have never used a command line should be familiar with.

#### B1. A Very Brief Introduction to R

Matthew C Keller, June 2021 Virtual Workshop

This lecture provides a broad overview of the R statistical language, the motivations for using it, the difference between class and mode of objects, and how a typical R session works.

#### Biometrical Genetics

#### C1. R Basics: Downloading and Installing R and RStudio

Elizabeth Prom-Wormley, June 2021 Virtual Workshop

Introduction to R Part 1. Students will receive a step-by-step approach to downloading R onto their computers, installing R, and installing RStudio as well as some basic background on how R works.

#### C2. R Basics: Finding, Opening, and Reviewing Files

Elizabeth Prom-Wormley, June 2021 Virtual Workshop

Introduction to R Part 2. It will walk students through using files within R and conducting preliminary investigations of the variables in a dataset within base R.

#### C3. R Basics: Data management

Elizabeth Prom-Wormley, June 2021 Virtual Workshop

Introduction to R Part 3. It will guide students through basic functions for data management within base R.

#### C4. R Basics: Graphics and Basic Statistics

Elizabeth Prom-Wormley, June 2021 Virtual Workshop

Introduction to R Part 4. It will guide students through basic functions for graphics and data visualization within base R.

#### C5. R Basics: Working with Twin Data

Elizabeth Prom-Wormley, June 2021 Virtual Workshop

This video will focus on working with twin data. In particular, this video will help students establish the basics of running basic analyses and visualizing twin data.

#### D1. Introduction to Python

Cotton Seed, June 2021 Virtual Workshop

Introduces the Python programming language.

#### E1. Introduction to Statistical Genetics

Benjamin Neale, June 2021 Virtual Workshop

Basic concepts in quantitative genetics, including Mendelian genetics, gene action (additive, dominant, recessive), heritability, liability threshold model, means, variances, structure of DNA, types of variants, whole-genome data.

#### F1. Introduction to Population Genetics

Alex Bloemendal, June 2021 Virtual Workshop

Basic concepts in population genetics, including nucleotide diversity, random genetic drift, effective population size, coalescent theory, time to common ancestor, site frequency spectrum, linkage disequilibrium, and principal components analysis.

#### G1. History of Quantitative Genetics

Lea Davis, June 2021 Virtual Workshop

This is a historical reflection on the scientific and personal context leading up to and including the publication of R.A. Fisher’s paper “The Correlation between Relatives on the Supposition of Mendelian Inheritance”.

#### H1. Introduction to Measured Genetic Variants

Katrina Grasby, June 2022 Virtual Workshop

This video presents key concepts including what a genetic variant is, DNA strand, ambiguous and unambiguous alleles. Types of genetic variation including SNPs, insertions and deletions, biallelic and multiallelic sites are described. The basics of acquiring sequence data and genotype data are introduced.

#### I1. History of Behavioral Genetics

Nick Martin, June 2021 Virtual Workshop

The historical context of modern human behaviour genetics and of this course itself is briefly described focussed on three core issues (i) how big do twin studies need to be, (ii) what is the effect of biassed sampling of twins from the population (iii) how to estimate the genetic and environmental contributions to correlations between two or more traits.

#### K1. Linear Regression and Modeling Genetic Covariance Structures

Conor Dolan, June 2021 Virtual Workshop

Basic concepts in regression, variance components, SEM and path diagrams, and fitting SEMs to twin data.

#### L1. Introduction to Structural Equation Modeling, Part 1: Overview

Michael C. Neale, June 2021 Virtual Workshop

The basics of variation - means and variances are considered, followed by description of i) the tracing rules of path analysis and ii) matrix representation of path models. The discussion is illustrated with a simple common factor model, and considers model identification. The 27-minute presentation concludes with rationale for always using Open Source software for scientific purposes, as using closed source code is inappropriate for science.

#### L2. Introduction to Structural Equation Modeling, Part 2: Likelihood

Michael C. Neale, June 2021 Virtual Workshop

This half-hour talk describes the specification of the ACE model that is widely used in human behavioral genetic studies. It considers how a model where a, c and e path coefficients are estimated differs from one where the variance components a2, c2 and e2 are directly estimated (plot spoiler: the latter allows variance components to go negative, which has less interpretability but better statistical properties).

#### M1. Hypothesis Testing, Effect Sizes, and Statistical Power

Brad Verhulst, June 2022 Virtual Workshop

Basic concepts in hypothesis testing, including effect sizes, type I and type II errors, calculation of statistical power, non-centrality parameter, and applications of these concepts to twin studies.

#### M2. Modeling ordinal data using a normal liability-threshold model

Brad Verhulst, June 2022 Virtual Workshop

Discusses conceptualization of categorical data as arising from a liability-threshold model.

#### N1. Estimating Changes in Genetic Effects across Age and Time

Dorret Boomsma, June 2021 Virtual Workshop

“Genes Over Time” can refer to the changes in genetic variance and heritability as we compare these across generations and time; it may also refer to differential gene expression as a function of age, i.e. genotype by age interaction. To establish if the same genes are expressed and whether their relative importance changes during the lifespan, multiple designs can be applied, including longitudinal studies with repeated measures on the same individuals (e.g. in the classical design) or multi-generation data (e.g. parent-twin studies).

#### O1. Latent Growth Curve Modeling Part 1

OpenMx TV, 2018, OpenMx TV YouTube channel

Discussion of fitting latent growth curves using OpenMx, Part 1.

#### O2. Latent Growth Curve Modeling Part 2

OpenMx TV, 2018, OpenMx TV YouTube channel

Discussion of fitting latent growth curves using OpenMx, Part 2

#### O3. Latent Growth Curve Modeling Part 3

OpenMx TV, 2018, OpenMx TV YouTube channel

Discussion of fitting latent growth curves using OpenMx, Part 3