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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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Toc

Table of Contents (11) Chapters Close

Preface 1. Python and the Surrounding Software Ecology 2. Next-generation Sequencing FREE CHAPTER 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

Exploring a dataset with Bio.PopGen

In this chapter, we will perform an initial exploratory analysis of one of our generated datasets. We will analyze the 10 percent sampling of chromosome 2 without the offspring. We will look for monomorphic loci (in this case, SNPs) across populations along with how to research minimum allele frequencies and expected heterozygosities.

Getting ready

You will need to have run the previous two recipes and should have the hapmap10_auto_noofs_2.gp and hapmap10_auto_noofs_2.pops files. We will also use the metadata file downloaded in the first recipe.

For this code to work, you will need to install Genepop from http://kimura.univ-montp2.fr/~rousset/Genepop.htm. We will use the interface provided by Biopython to execute Genepop and parse its output files.

There is a notebook with this recipe: 03_PopGen/Exploratory_Analysis.ipynb, but it will still require running the previous two notebooks in order for the required files to be generated.

How to do it…

Take...

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