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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

By : Tiago Antao
3.5 (4)
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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

3.5 (4)
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 (12 chapters)
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Inferring shared chromosomal segments with Germline


The discovery of shared chromosomal segments among individuals can have many applications: finding relationships across individuals, estimating strong bottlenecks, or possible signals of selection.

To execute this recipe, we will use Germline, which is an efficient tool for performing the inference of shared chromosomal segments. It requires phased data. Phased data allows you to assign genotyped data to a specific chromosome, that is, instead of having a list of genotype calls per position, we end up with reconstructed haplotypes.

Getting ready

The preparation of data requires some work. First, we must provide the final phased haplotypes for our dataset in the notebook directory so that you can skip the following process, save for the trivial download of integrated_call_samples.20101123.ped. The directory from the repository is Chapter10. The Notebook is Germline.ipynb, the data file is good.match.gz, and the code support files are merge...

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