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  • Book Overview & Buying Bioinformatics with Python Cookbook
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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

By : Tiago R Antao, Tiago Antao
4.7 (6)
Buy this Book
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Bioinformatics with Python Cookbook

Bioinformatics with Python Cookbook

4.7 (6)
By: Tiago R Antao, Tiago Antao
Buy this Book

Overview of this book

If you have intermediate-level knowledge of Python and are well aware of the main research and vocabulary in your bioinformatics topic of interest, this book will help you develop your knowledge further.
Table of Contents (11 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Sections
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Conventions
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Reader feedback
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Customer support
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1
1. Python and the Surrounding Software Ecology
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1. Python and the Surrounding Software Ecology
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Introduction
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Installing the required software with Anaconda
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Installing the required software with Docker
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Interfacing with R via rpy2
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Performing R magic with IPython
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2. Next-generation Sequencing
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2. Next-generation Sequencing
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Introduction
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Accessing GenBank and moving around NCBI databases
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Performing basic sequence analysis
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Working with modern sequence formats
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Working with alignment data
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Analyzing data in the variant call format
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Studying genome accessibility and filtering SNP data
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3. Working with Genomes
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3. Working with Genomes
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Introduction
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Working with high-quality reference genomes
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Dealing with low-quality genome references
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Traversing genome annotations
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Extracting genes from a reference using annotations
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Finding orthologues with the Ensembl REST API
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Retrieving gene ontology information from Ensembl
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4. Population Genetics
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4. Population Genetics
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Introduction
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Managing datasets with PLINK
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Introducing the Genepop format
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Exploring a dataset with Bio.PopGen
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Computing F-statistics
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Performing Principal Components Analysis
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Investigating population structure with Admixture
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5. Population Genetics Simulation
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5. Population Genetics Simulation
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Introduction
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Introducing forward-time simulations
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Simulating selection
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Simulating population structure using island and stepping-stone models
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Modeling complex demographic scenarios
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Simulating the coalescent with Biopython and fastsimcoal
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6. Phylogenetics
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6. Phylogenetics
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Introduction
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Preparing the Ebola dataset
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Aligning genetic and genomic data
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Comparing sequences
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Reconstructing phylogenetic trees
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Playing recursively with trees
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Visualizing phylogenetic data
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7. Using the Protein Data Bank
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7. Using the Protein Data Bank
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Introduction
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Finding a protein in multiple databases
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Introducing Bio.PDB
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Extracting more information from a PDB file
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Computing molecular distances on a PDB file
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Performing geometric operations
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Implementing a basic PDB parser
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Animating with PyMol
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Parsing mmCIF files using Biopython
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8. Other Topics in Bioinformatics
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8. Other Topics in Bioinformatics
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Introduction
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Accessing the Global Biodiversity Information Facility
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Geo-referencing GBIF datasets
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Accessing molecular-interaction databases with PSIQUIC
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Plotting protein interactions with Cytoscape the hard way
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9. Python for Big Genomics Datasets
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9. Python for Big Genomics Datasets
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Introduction
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Setting the stage for high-performance computing
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Designing a poor human concurrent executor
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Performing parallel computing with IPython
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Computing the median in a large dataset
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Optimizing code with Cython and Numba
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Programming with laziness
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Thinking with generators
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Index
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Index

Extracting genes from a reference using annotations

In this recipe, we will see how to extract a gene sequence with the help of an annotation file to get its coordinates against a reference FASTA. We will use the Anopheles gambiae genome, along with its annotation file (as per the previous two recipes). We will first extract the Voltage-gated sodium channel (VGSC) gene, which is involved in resistance to insecticides.

Getting ready

If you have followed the previous two recipes, you are ready. If not, download the Anopheles gambiae FASTA file, along with the GTF file. You also need to prepare the gffutils database:

import gffutils
import sqlite3
try:
    db = gffutils.create_db('gambiae.gff.gz', 'ag.db')
except sqlite3.OperationalError:
    db = gffutils.FeatureDB('ag.db')

As usual, you will find all this in the 02_Genomes/Getting_Gene.ipynb notebook.

How to do it…

Let's take a look at the following steps:

  1. Let's start by retrieving the annotation information...

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