Bioinformatics with Python Cookbook - Second Edition

How to do it...

Take a look at the following steps:

1. First, let's define our k (a number of ancestral populations) range of interest, as follows:

k_range = range(2, 10)  # 2..9

2. Let's run admixture for all our ks (alternatively, you can skip this step and use the example data provided):

for k in k_range:    os.system('admixture --cv=10 hapmap10_auto_noofs_ld.bed %d > admix.%d' % (k, k))

This is the worst possible way of running admixture and will probably take more than 3 hours if you do it like this. This is because it will run all ks from two to nine in a sequence. There are two things that you can do to speed this up: use the multithreaded option (-j), which admixture provides, or run several applications in parallel. Here, I have to assume ...