add individual statistics (eg heterozygosity)

Something like

def individual_heterozygosity(ts, ind):
   ts.pairwise_diversity(ind.nodes)

should do it - very simple, but we want to make it easy and natural for people to deal with individuals.

[castedo]

So wrapping up on the scope of this:

• A) add function(s) in the Python API with “heterozygosity” in the name

With @petrelharp’s observed_heterozygosity Python example, I’ve got a great specification for A), thanks! The name is unambiguous and matches nicely and in an analogous way to all the other stats functions.

• A.i) make sure works for non-autosomal chromosome pairs (e.g. X&Y, W&Z)

Handling sex chromosomes is way out of scope right now. There are challenging issues in trying to deal with this and I’ll not worry about.

• B) define and code a function which generalizes heterozygosity to non-diploid species

“observed heterozygosity” has a consistent meaning in the field (I think, I hope!) and @petrelharp’s clatification is a totally logical extension of it and NaN is the value for monoploids. (As a side note, this definition of heterozygosity seems sensible for diploids, because it has a max value of 1. But it seem wonky to me to use it rather than ‘gene diversity’ (see #961), as a statistic to use across many types of ploidy. Just a sort of esthetic personal reaction.)

• C) add function(s) in the Python API with “F_IT” and “F_IS” in the name

Hammer out the details in (or after) #858 and make a separate GitHub issue to track implementing F_IT and F_IS.

• D) enhance documentation and Python API to show how many individual-based statistics can be achieved with “efficient building blocks” of the API

This is too hard to hash out now in Github issues. More appropriate for brainstorming face-(to-screen-to-)face and/or after all this other stuff become more clear.

[petrelharp]

As this is showing up in the SLiM list, here’s how to compute individual heterozygosities:

ts.diversity([i.nodes for i in ts.individuals()])