Bioinformatics Data Skills : Reproducible and Robust Research with Open Source Tools

Vince Buffalo

ISBN 10: 1449367372 / ISBN 13: 9781449367374

Published by O'reilly Media Aug 2015, 2015

About this Item

Neuware - This practical book teaches the skills that scientists need for turning large sequencing datasets into reproducible and robust biological findings. Many biologists begin their bioinformatics training by learning languages like Perl and R alongside the Unix command line. But there's a huge gap between knowing a few programming languages and being prepared to analyze large amounts of biological data.Rather than teach bioinformatics as a set of workflows that are likely to change with this rapidly evolving field, this book demsonstrates the practice of bioinformatics through data skills. Rigorous assessment of data quality and of the effectiveness of tools is the foundation of reproducible and robust bioinformatics analysis. Through open source and freely available tools, you';ll learn not only how to do bioinformatics, but how to approach problems as a bioinformatician.Go from handling small problems with messy scripts to tackling large problems with clever methods and toolsFocus on high-throughput (or 'next generation') sequencing dataLearn data analysis with modern methods, versus covering older theoretical conceptsUnderstand how to choose and implement the best tool for the jobDelve into methods that lead to easier, more reproducible, and robust bioinformatics analysis.

Seller Inventory # 9781449367374

Bibliographic Details

• Title: Bioinformatics Data Skills : Reproducible and Robust Research with Open Source Tools
• Publisher: O'reilly Media Aug 2015
• Publication Date: 2015
• Language: English
• ISBN 10: 1449367372
• ISBN 13: 9781449367374
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 233W x 177H x 35D millimeters 233 millimeters width by 177 millimeters height by 35 millimeters depth
• Weight: 929 grams

About this title

Synopsis

Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youâ??ll learn how to use freely available open source tools to extract meaning from large complex biological data sets.

At no other point in human history has our ability to understand lifeâ??s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, youâ??re ready to get started.

• Go from handling small problems with messy scripts to tackling large problems with clever methods and tools
• Process bioinformatics data with powerful Unix pipelines and data tools
• Learn how to use exploratory data analysis techniques in the R language
• Use efficient methods to work with genomic range data and range operations
• Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM
• Manage your bioinformatics project with the Git version control system
• Tackle tedious data processing tasks with with Bash scripts and Makefiles

About the Author

Vince Buffalo is currently a first-year graduate student studying population genetics in Graham Coop's lab at UC Davis in the Population Biology Graduate Group. Before starting his PhD in population genetics, Vince worked professionally as a bioinformatician in the Bioinformatics Core at the UC Davis Genome Center and in the Department of Plant Sciences. An obsessive programmer since he was a young teenager, Vince was drawn to the statistical and computational problems of genomics. He works on open source bioinformatics tools in his work and free time, and enjoys fly fishing and cooking when away from the computer.