Lositan

A selection detection workbenchbased on a Fst outlier method

Tiago AntaoLiverpool School of Tropical Medicine

The question

Detect loci under selection

Why? To do some analysis that require neutral loci (i.e.,

you have to remove loci under selection). Most of the analysis presented here require this

You actually want to know loci under selection Put your own reason here...

As per Gordon's presentation...

A solution

An Fst-outlier method (Beaumont and Nichols 1996) where an area (Fst and heterozygosity) where neutral markers are supposed to fall is calculated.

It is up to you to decide if you trust this method (especially in the context of your datasets)!

The method - I

A coalescent simulation Neutral Island model A bunch of loci (many thousands)

You get an area where neutral markers are supposed to fall...

The method - II

What you need to supply?

How many populations you have How many populations exist The mutation model The neutral Fst from your data

Migration for the island model is calculated from the Fst

Lositan

Doubles as... Easy to use interface compared to the original

implementation Fdist is command-line, prone to errors Fdist has its own data file format

Sorts out a few practical problems with deviations from theory We will get back to this

Lets give it a try...

Sorting a few issues

The neutral Fst of your data is not easy to compute In the initial dataset

candidate selected loci are used to calculate the neutral Fst

Lositan removes them when computing “neutral” Fst

The Fst formula:

is only valid for infinite populations and the infinite alleles model

This means that fdist might fail to simulate your Fst

Lositan forces the correct FstLets correct it...

Limitations

No support for the dominant variation Thousands of markers and thousands of

individuals not supported Strict Genepop parsing (not a limitation)