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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789344691
Length 360 pages
Edition 2nd Edition
Languages
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Author (1):
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Tiago Antao Tiago Antao
Author Profile Icon Tiago Antao
Tiago Antao
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Table of Contents (12) Chapters Close

Preface 1. Python and the Surrounding Software Ecology FREE CHAPTER 2. Next-Generation Sequencing 3. Working with Genomes 4. Population Genetics 5. Population Genetics Simulation 6. Phylogenetics 7. Using the Protein Data Bank 8. Bioinformatics Pipelines 9. Python for Big Genomics Datasets 10. Other Topics in Bioinformatics 11. Advanced NGS Processing

Processing NGS data with HTSeq

HTSeq (https://htseq.readthedocs.io) is an alternative library that's used for processing NGS data. Most of the functionality made available by HTSeq is actually available in other libraries covered in this book, but you should be aware of it as an alternative way of processing NGS data. HTSeq supports, among others, FASTA, FASTQ, SAM (via pysam), VCF, GFF, and Browser Extensible Data (BED) file formats. It also includes a set of abstractions for processing (mapped) genomic data, encompassing concepts like genomic positions and intervals or alignments. A complete examination of the features of this library is beyond our scope, so we will concentrate on a small subset of features. We will take this opportunity to also introduce the BED file format.

The BED format allows for the specification of features for annotations tracks. It has many...

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