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)

Finding orthologues with the Ensembl REST API

In this recipe, we will learn how to look for orthologues for a certain gene. This simple recipe will not only introduce orthology retrieval but also how to use REST APIs on the web to access biological data. Last, but surely not least, it will serve as an introduction to how to access the Ensembl database using the programmatic API.

In our example, we will try to find any orthologue for the human lactase (LCT) gene on the horse genome.

Getting ready

This recipe will not require any pre-downloaded data, but since we are using web APIs, internet access will be needed. The amount of data that can be transferred will be limited.

We will also make use of the requests library to access Ensembl. The request API is an easy-to-use wrapper for web requests. Of course, you can use the standard Python libraries, but these are much more cumbersome.

As usual, you can find this content in the Chapter05/Orthology.py notebook file.

How...