Chapter 29 Topics in pop gen

This is just a bunch of ideas. But basically, I want to have some topics here that everyone should know about. Slanted toward things that are relevant for inference or simulation.

29.1 Coalescent

Gotta have a lecture on the coalescent. It would be nice to try to motivate all the topics from this backward in time perspective.

Get far enough to discuss \(\pi\) and the expected site frequency spectrum.

29.2 Measures of genetic diversity and such

It would really be good for me to write a chapter / give a few lectures on different measures like dxy and fst

From Ash’s paper: However, population genomic analyses (outlined below) use FST only, as dxy was highly correlated to nucleotide diversity (for early stage diverging populations the correlation between dxy and \(\pi\) is > 0.91, Pearson correlation). As such variation in dxy across the genome reflects variation in diversity, not differentiation (Riesch et al., 2017).

Tajima’s \(D\) and such. The influence of selection on such measures.

29.3 Demographic inference with \(\partial a \partial i\) and moments

29.4 Balls in Boxes

Would be worthwhile to have a review of all these sorts of variants of population assignment, structure, admixture, etc.

Population structure and PCAs.

finestructure and fineRADstructure.

Might want to insert Bradburd, Coop, and Ralph (2018).

Might also want to discuss Pickrell and Pritchard (2012).

Also: Pritchard, Stephens, and Donnelly (2000)

What if we go and try to put the same one in? Like Pritch 2000 again: (Pritchard, Stephens, and Donnelly 2000)

29.5 Some landscape genetics

After talking with Amanda about her dissertation I realized it would be good to talk about some landscape genetics stuff. For sure I want to talk about EEMS and maybe CircuitScape, just so I know well what is going on with the latter.

29.6 Relationship Inference

Maybe do a lecture on this…

29.7 Tests for Selection

A look at a selection of the methods that are out there. FST outliers, Bayescan, Lositan, PCAdapt, and friends. It would be good to get a nice succinct explanation/understanding of all of these.

29.8 Multivariate Associations, GEA, etc.

It really is time for me to wrap my head around this stuff.

29.9 Estimating heritability in the wild

Another from Amanda. It would be good to do some light Quant Genet so that we all understand how we might be able to use NGS data to estimate heritability in wild populations.


Bradburd, Gideon S., Graham M. Coop, and Peter L. Ralph. 2018. “Inferring Continuous and Discrete Population Genetic Structure Across Space.” Genetics 210 (1): 33–52.
Pickrell, Joseph K., and Jonathan K. Pritchard. 2012. “Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data.” PLOS Genetics 8 (11): e1002967.
Pritchard, Jonathan K., Matthew Stephens, and Peter Donnelly. 2000. Inference of Population Structure Using Multilocus Genotype Data.” Genetics 155 (2): 945–59.