Analyzing population structure

Previously, we introduced data analysis with sgkit ignoring the population structure. Most datasets, including the one we are using, actually do have a population structure. Sgkit provides functionality to analyze genomic datasets with population structure and that is what we are going to investigate here.

Getting ready

You will need to have run the first recipe, and should have the hapmap10_auto_noofs_ld data we produced and also the original population meta data relationships_w_pops_041510.txt file downloaded. There is a Notebook file with the 06_PopGen/Pop_Stats.py recipe in it.

How to do it...

Take a look at the following steps:

1. First, let’s load the PLINK data with sgkit:

   from collections import defaultdict
   from pprint import pprint
   import numpy as np
   import matplotlib.pyplot as plt
   import seaborn as sns
   import pandas as pd
   import xarray as xr
   import sgkit as sg
   from sgkit.io import plink
    
   data = plink.read_plink(path=...