We are now ready to start exploring the data with the objective of finding some rules on how to filter it. Because we have a lot of annotations to explore (in our case, we reduced them, but generally, that would be the case), we need to find a place to start. It can be daunting to go out on a blind fishing expedition. My personal preference for a first approach is using a machine learning technique called decision trees. Decision trees will suggest what the fundamental annotations segregating the data in correct and error calls are. Another advantage of decision trees is that they barely need any data preparation, as opposed to many other machine learning techniques.
Bioinformatics with Python Cookbook - Second Edition
By :
Bioinformatics with Python Cookbook - Second Edition
By:
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
Free Chapter
Python and the Surrounding Software Ecology
Next-Generation Sequencing
Working with Genomes
Population Genetics
Population Genetics Simulation
Phylogenetics
Using the Protein Data Bank
Bioinformatics Pipelines
Python for Big Genomics Datasets
Other Topics in Bioinformatics
Advanced NGS Processing
Index
Customer Reviews