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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

Finding genomic features from sequencing annotations

We will conclude this chapter and this book with a simple recipe that suggests that sometimes you can learn important things from simple unexpected results, and that apparent quality issues might mask important biological questions.

We will plot read depth – DP – across chromosome arm 2L for all the parents on our crosses. The recipe can be found in Chapter04/2L.py.

How to do it…

We’ll get started with the following steps:

  1. Let’s start with the usual imports:
    from collections import defaultdict
    import gzip
    import numpy as np
    import matplotlib.pylab as plt
  2. Let’s load the data that we saved in the first recipe:
    num_parents = 8
    dp_2L = np.load(gzip.open('DP_2L.npy.gz', 'rb'))
    print(dp_2L.shape)
  3. And let’s print the median DP for the whole chromosome arm, and a part of it in the middle for all parents:
    for i in range(num_parents):
       ...
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