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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 Nov 2018
Publisher Packt
ISBN-13 9781789344691
Length 360 pages
Edition 2nd 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 (12) 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. Bioinformatics Pipelines 9. Python for Big Genomics Datasets 10. Other Topics in Bioinformatics 11. Advanced NGS Processing

Simulating selection

We will now perform an example of simulating selection with simuPOP. We will perform a simple case with dominant mutation on a single locus, along with a complex case with two loci using epistatic effects. The epistatic effect will have a required mutation on a main SNP. While this mutation is required to confer advantage, another mutation on another SNP adds up to the previous one (but does nothing on its own); this was inspired by the very real case of malarial resistance to the Sulfadoxine/Pyrimethamine drug, which always requires a mutation on the Dihydrofolate Reductase (DHFR) gene, which can be enhanced with a mutation on the Deoxyhypusine Synthase (DHPS) gene. If you are interested in finding out more, refer to the Origin and Evolution of Sulfadoxine Resistant Plasmodium falciparum article from Vinayak et al. on PLOS Pathogens at http://journals.plos...

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