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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

By : Tiago Antao
4 (8)
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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

4 (8)
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)
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Doing metagenomics with QIIME 2 Python API

Wikipedia says that metagenomics is the study of genetic material that’s recovered directly from environmental samples. Note that “environment” here should be interpreted broadly: in the case of our example, we will deal with gastrointestinal microbiomes in a study of a fecal microbiome transplant in children with gastrointestinal problems. The study is one of the tutorials of QIIME 2, which is one of the most widely used applications for data analysis in metagenomics. QIIME 2 has several interfaces: a GUI, a command line, and a Python API called the Artifact API.

Tomasz Kościółek has an outstanding tutorial for using the Artifact API based on the most well-developed (client-based, not artifact-based) tutorial on QIIME 2, the “Moving Pictures” tutorial (http://nbviewer.jupyter.org/gist/tkosciol/29de5198a4be81559a075756c2490fde). Here, we will create a Python version of the fecal microbiota...

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