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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Use modern Python libraries and applications to solve real-world computational biology problems

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803236421
Length 360 pages
Edition 3rd Edition
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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 (15) Chapters Close

Preface 1. Chapter 1: Python and the Surrounding Software Ecology 2. Chapter 2: Getting to Know NumPy, pandas, Arrow, and Matplotlib FREE CHAPTER 3. Chapter 3: Next-Generation Sequencing 4. Chapter 4: Advanced NGS Data Processing 5. Chapter 5: Working with Genomes 6. Chapter 6: Population Genetics 7. Chapter 7: Phylogenetics 8. Chapter 8: Using the Protein Data Bank 9. Chapter 9: Bioinformatics Pipelines 10. Chapter 10: Machine Learning for Bioinformatics 11. Chapter 11: Parallel Processing with Dask and Zarr 12. Chapter 12: Functional Programming for Bioinformatics 13. Index 14. Other Books You May Enjoy

Population Genetics

Population genetics is the study of the changes in the frequency of alleles in a population on the basis of selection, drift, mutation, and migration. The previous chapters focused mainly on data processing and cleanup; this is the first chapter in which we will actually infer interesting biological results.

There is a lot of interesting population genetics analysis based on sequence data, but as we already have quite a few recipes for dealing with sequence data, we will divert our attention elsewhere. Also, we will not cover genomic structural variations such as Copy Number Variations (CNVs) or inversions here. We will concentrate on analyzing SNP data, which is one of the most common data types. We will perform many standard population genetic analyses with Python, such as using the Fixation Index (FST) with computing F-statistics, Principal Components Analysis (PCA), and studying population structure.

We will use Python mostly as a scripting language that...

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