Book Image

Bioinformatics with Python Cookbook - Third Edition

By : Tiago Antao
Book Image

Bioinformatics with Python Cookbook - Third Edition

By: Tiago Antao

Overview of this book

Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data, and this book will show you how to manage these tasks using Python. This updated third edition of the Bioinformatics with Python Cookbook begins with a quick overview of the various tools and libraries in the Python ecosystem that will help you convert, analyze, and visualize biological datasets. Next, you'll cover key techniques for next-generation sequencing, single-cell analysis, genomics, metagenomics, population genetics, phylogenetics, and proteomics with the help of real-world examples. You'll learn how to work with important pipeline systems, such as Galaxy servers and Snakemake, and understand the various modules in Python for functional and asynchronous programming. This book will also help you explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks, including Dask and Spark. In addition to this, you’ll explore the application of machine learning algorithms in bioinformatics. By the end of this bioinformatics Python book, you'll be equipped with the knowledge you need to implement the latest programming techniques and frameworks, empowering you to deal with bioinformatics data on every scale.
Table of Contents (15 chapters)

A showcase of Python’s functools module

Python has three built-in modules that greatly help when writing code in a functional dialect: functools, operator, and itertools. In this recipe, we are going to briefly discuss the functools module. For example, the fundamental reduce function (where part of the name of MapReduce comes from) is only available if you import functools.

While a detailed exploration of these modules would be too long for a single recipe, we are going to showcase some functionality by improving some of the code of the previous recipes with the functionality from functools and showcase some illustrative examples of the utility of the module.

Getting ready

Our code is available in Chapter12/ We will make references to previous recipes.

How to do it...

Let’s look at several illustrative examples:

  1. Remember that our recursive implementation of a factorial function in the previous recipe was not very efficient? Let’...