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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781782175117
Length 306 pages
Edition 1st Edition
Languages
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Author (1):
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Tiago Antao Tiago Antao
Author Profile Icon Tiago Antao
Tiago Antao
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Table of Contents (16) Chapters Close

Bioinformatics with Python Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Python and the Surrounding Software Ecology FREE CHAPTER 2. Next-generation Sequencing 3. Working with Genomes 4. Population Genetics 5. Population Genetics Simulation 6. Phylogenetics 7. Using the Protein Data Bank 8. Other Topics in Bioinformatics 9. Python for Big Genomics Datasets Index

Simulating population structure using island and stepping-stone models


We will now simulate population structure. Let's start with an island model and then create a one-dimensional stepping-stone model. We will also study FST and distinguish between deme-level statistics and meta-population level statistics. Strictly speaking, we will simulate fragmentation models by splitting into islands or stepping-stones.

Getting ready

Read the first recipe (Introducing forward-time simulations) as it introduces the basic programming framework. If you are using notebooks, the content is in 04_PopSim/Pop_Structure.ipynb.

How to do it…

Take a look at the following steps:

  1. Let's start with some basic code from the first recipe:

    from __future__ import division
    from collections import defaultdict, OrderedDict
    from copy import deepcopy
    import simuPOP as sp
    from simuPOP import demography
    num_loci = 10
    pop_size = 50
    num_gens = 101
    num_pops = 10
    migs = [0, 0.005, 0.01, 0.02, 0.05, 0.1]
    init_ops = OrderedDict()
    pre_ops...
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