Population genetics, computational methods, and accessible software distribution
The cookbooks are step-by-step tutorials for Migrate 7 and Migrate 6.1. Each recipe covers one kind of analysis and comes with its data sets, parameter files, menu screens and annotated output, so you can repeat every run yourself. Most recipes use simulated data with known true values, so you can check the estimates.
The recipes are being written over the coming weeks. Recipes marked draft are incomplete and may change. Each recipe page links to a ZIP archive with all of its input files and scripts. Start with 00 Basics. Recipes on unphased data (haplotyping) and on the fractional coalescent are planned.
The cookbooks are supported by the U.S. National Science Foundation award DBI 2549631, Population genetic inference software for the genomic age.
Draft
This recipe runs Migrate with its default settings on four small simulated data sets: one and two populations, DNA sequences and microsatellites. It explains the input files, the menu, the parmfile, and every file a run writes. Because the data are simulated, we know the true values and can check the estimates.
Open recipe: 00 Basics: input files, a first run, and the output
Complete
This recipe uses one simulated data set from three island populations and analyses it with different migration models: every rate free, some rates zero, symmetric rates, and the n-island model. It shows how to write the migration matrix, how to compare the models, and how to choose between M and the number of immigrants 4Nm. Read 00-basics first.
Draft
This recipe estimates when populations split. It uses two simulated data sets: two populations that split once, and three populations that split one after the other. It shows how to write a split in the migration matrix, with and without gene flow after the split, how to read the divergence parameters, how their priors matter, and how to compare population trees. Read 00-basics and 01-migration first.
Draft
This recipe estimates exponential growth. It uses simulated data sets: one population that grows, one at constant size, one that shrinks, and two populations of which one grows. It shows how to switch growth on, how to read the growth rate, why its estimate is biased upward and how more loci fix that, how to test whether a population grows at all, and applies this to a real mitochondrial data set of a frog. Read 00-basics and 01-migration first.
Draft
This recipe estimates how Theta and M change through time. Migrate has two skylines: an empirical one, read from the sampled genealogies of an ordinary run, and a parametric one (skyline=PARAM), in which Theta or M get a multiplier per time segment that is estimated with the other parameters. The data are simulated: a constant population, one that expanded, one that declined, the expansion with ancient samples (tip dates), and two populations whose migration rate changed. Read 00-basics, 01-migration and 03-growth first; section 6 uses the tip dates of 02-divergence.
Open recipe: 04 Skyline: population sizes and migration rates through time
Draft
Which migration model fits the data better: one with migration in both directions, one with equal rates, or one with migration in one direction only? Migrate answers this with the marginal likelihood of each model and Bayes factors. This recipe shows where the marginal likelihoods are in the outfile, checks the four estimators against an exact value, and then asks how often they pick the true model in simulated data, and how many heated chains that needs. Read 00-basics and 01-migration first.
Open recipe: 05 Model selection: marginal likelihoods and heating
Draft
Some individuals in a data set may have no known population: a bird caught between forests, a sample with a lost label, a possible migrant. Migrate can estimate where such individuals come from while it estimates the population sizes and migration rates. This recipe shows how to mark them, how to read the assignment table, how well assignment works in simulated data, and applies it to the Taita thrush, a bird living in three forest fragments in Kenya. Read 00-basics and 01-migration first.