Book Image

Bioinformatics with Python Cookbook - Second Edition

By : Tiago Antao
Book Image

Bioinformatics with Python Cookbook - Second 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. This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries. This book will help you get a better understanding of working with a Galaxy server, which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark. By the end of this book, you'll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data.
Table of Contents (16 chapters)
Title Page
About Packt
Contributors
Preface
Index

Preparing a dataset for phylogenetic analysis


In this recipe, we will download and prepare the dataset to be used for our analysis. The dataset contains complete genomes of the Ebola virus. We will use DendroPy to download and prepare the data.

Getting ready

We will download complete genomes from GenBank; these genomes were collected from various Ebola outbreaks, including several from the 2014 outbreak. Note that there are several virus species that cause the Ebola virus disease; the species involved in the 2014 outbreak (the EBOV virus, formally known as the Zaire Ebola virus) is the most common, but this disease is caused by more species of the genus Ebolavirus; four others are also available in sequenced form. You can read more at https://en.wikipedia.org/wiki/Ebolavirus.

If you have already gone through the previous chapters, you may panic looking at the potential data sizes involved here; this is not a problem at all because these are genomes of viruses that are around 19 kbp in size...