This set of notes covers estimating viabilities (relative and absolute) and the basic properties of genetic drift, including the inbreeding analogy to drift, inbreeding and variance effective population sizes, the interaction of mutation and drift, the interaction of migration and drift, and the interaction of natural selection (specifically viability selection) and drift.
Updated notes on STRUCTURE and on natural selection
I have just posted revised notes on the analysis of population structure using individual assignment, focusing on STRUCTURE. I’ve also posted revised notes on the basic principles of natural selection, focusing on viability selection at one locus with two alleles. If you’ve seen earlier versions of either set of notes, you won’t find much new here – other than a few more lame jokes hidden in the footnotes.
- Analyzing the genetic structure of populations: individual assignment (HTML) (PDF)
- The genetics of natural selection (HTML) (PDF)
By the way, I haven’t mentioned this yet, but my goal is to finish revising these notes no later than mid-August, earlier if I can pull it off. When I’ve revised all of them, I’ll compile them into a single volume of notes and release a new version of Lecture notes in population genetics. I have to say that when I was looking up the URL for the last edition of my notes on Figshare, I was surprised to see that they’ve been seen nearly 11,000 times and been downloaded nearly 3400 times. I am pleased that so many people seem to find them useful. If you’re one of those people and you have suggestions on how to make them more useful, please let me know. I am especially interested in hearing from you if you find errors or discussions that are confusing.
Notes on a Bayesian approach for analysis of F-statistics
If you follow me on Twitter or read Uncommon Ground, you may remember that I announced last September that I’d written a new version of Hickory (a C++ program that Paul Lewis and I wrote) using R and Stan for Bayesian analysis of Wright’s F-statistics. This set of notes outlines the basic principle behind the approach and provides an overview of using Hickory for analysis of F-statistics. Hickory can do more than is illustrated here. If you’re interested, visit the Github page. If you’re really interested, follow the instructions there to install it as a package in R.