
Multisite, multivariate genetic analysis: simulation and analysis
The email wasn’t a challenge but a simple question: Is it possible to run a multivariate analysis in multiple sites? I was going to answer yes, of course, and leave it there but it would be a cruel, nonsatisfying answer. We can get a better handle of the question if we use a simple example; […]

Overlay of design matrices in genetic analysis
I’ve ignored my quantitative geneticist side of things for a while (at least in this blog) so this time I’ll cover some code I was exchanging with a couple of colleagues who work for other organizations. It is common to use diallel mating designs in plant and tree breeding, where a small number of parents […]

Suicide statistics and the Christchurch earthquake
Suicide is a tragic and complex problem. This week New Zealand’s Chief Coroner released its annual statistics on suicide, which come with several tables and figures. One of those figures refers to monthly suicides in the Christchurch region (where I live) and comes with an interesting comment: Suicides in the Christchurch region (Timaru to Kaikoura) […]

R, Julia and genome wide selection
— “You are a pussy” emailed my friend. — “Sensu cat?” I replied. — “No. Sensu chicken” blurbed my now exfriend. What was this about? He read my post on R, Julia and the shiny new thing, which prompted him to assume that I was the proverbial old dog unwilling (or was it unable?) to […]

Simulating data following a given covariance structure
Every year there is at least a couple of occasions when I have to simulate multivariate data that follow a given covariance matrix. For example, let’s say that we want to create an example of the effect of collinearity when fitting multiple linear regressions, so we want to create one variable (the response) that is […]