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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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Toc

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

Understanding pure functions

A pure function has a couple of important properties: for the same inputs, it produces the same outputs, and it has no side effects (it doesn’t change global variables and doesn’t do I/O). In this recipe, we are going to introduce a few simple examples to make the concept clear. We are mostly – but not exclusively – interested in the second property: the lack of side effects. In later recipes, it will be made clear why pure functions can be quite useful.

We are going to develop a very simple example where we are counting the genes sequenced per sample. We will have a database on a text file with counts for genes. For example, we might have sequenced LCT and TP53 on a sample, and LCT, MRAP2, and POMC on another. The total count would be: TP53: 1, LCT: 2, MRPA2: 1, and POMC: 1. We will be using a CSV file that can be easily read with Pandas or even just the CSV module.

Getting ready

We will be using a simple CSV file...

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