Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools 1st Edition

by Vince Buffalo (Author)

97 ratings

ISBN-13: 978-1449367374

ISBN-10: 1449367372

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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 scripting languages like Python 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 tools
Focus on high-throughput (or "next generation") sequencing data
Learn data analysis with modern methods, versus covering older theoretical concepts
Understand how to choose and implement the best tool for the job
Delve into methods that lead to easier, more reproducible, and robust bioinformatics analysis

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Editorial Reviews

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.

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Product details

Publisher ‏ : ‎ O'Reilly Media; 1st edition (August 18, 2015)
Language ‏ : ‎ English
Paperback ‏ : ‎ 536 pages
ISBN-10 ‏ : ‎ 1449367372
ISBN-13 ‏ : ‎ 978-1449367374
Item Weight ‏ : ‎ 1.9 pounds
Dimensions ‏ : ‎ 7 x 1.09 x 9.19 inches

Best Sellers Rank: #420,140 in Books (See Top 100 in Books)
- #76 in Bioinformatics (Books)
- #302 in Biochemistry (Books)
- #906 in Software Development (Books)

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5 star		71%
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2 star		2%
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Top reviews from the United States

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L. Zhou

Covers mot (all) of the basic skills at the intermediate level

Reviewed in the United States on August 31, 2020

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It's one of the most readable books in bioinformatics. It's concise and has a nice balance of range vs. depth.

The author is very adept at leading the audience into a topic in a step-by-step fashion, probably due to his experience in interacting with people who want to get into bioinformatics but only have very limited knowledge of unix and programing. For instance, although he pointed out that SQL was beyond the scope of this book, he nonetheless introduced a series of sqlite operations that should suffice for most research projects except those aiming at providing complex database for large group.

Highly recommended for scientists with background in biology but want to get into data analysis.

2 people found this helpful

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Solanacea

great book, not for beginners though

Reviewed in the United States on August 29, 2019

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This book contains a lot of tidbits of info I wish I knew when I started learning bioinformatics. I wouldn't really say it's a cookbook that'll take you through your analysis step by step, nor is it for beginners; but it teaches practical knowledge and good data analysis and record keeping practices. It's a little densely written, and definitely not a primary resource, but a good reference nonetheless.

3 people found this helpful

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Great reference for beginning unix and remote machine skills for bioinformatics

Reviewed in the United States on December 8, 2019

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I definitely recommend this book. I've started doing more bioinformatics at work. This chapters on unix tools and remote machines were directly applicable to the work I do, and they're mostly arranged in the order you would need them in. I also quite appreciate his editorializing on how to set up directory structures for more reproducible research.

The negative I would say is that I've had trouble motivating myself to go through the middle third of the book ("Introduction to R" and "Range Data") chapters. While proper programmers can and do float easily among languages, and I strongly appreciate the Unix chapters, it feels like people fall more into R or Python camps, and while I could be wrong, I don't feel like I should really need to add R at this time.

One person found this helpful

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Kevin Chen

A great book to start bioinformatics

Reviewed in the United States on March 24, 2020

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It introduce all the skills needed to work on the state of art NGS data, and present the skills in a very readable way.

2 people found this helpful

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Pdimens

A must read for early bioinformaticians

Reviewed in the United States on June 26, 2020

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Such a well written and easy to follow book for bioinformaticians with low-intermediate programming knowledge. I recommend this book to all of my mentees.

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N.R. Voss

nice range of topics

Reviewed in the United States on October 13, 2016

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Chose this book for a class in bioinformatics,

Pros: great range of topics covered: bash shell, git, ssh, working with data, data compression

Cons: the author is a little long winded and and it does not have great examples

4 people found this helpful

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Piotr

Great resource for learning your way around linux based systems ...

Reviewed in the United States on April 3, 2017

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Great resource for learning your way around linux based systems in relation to bioinformatics/genomic analysis tools. Everything is followed through step-by-step and doesn't leave you wondering why something was done, while at the same time it doesn't keep teaching you past commands unnecessarily.

One person found this helpful

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Cliente de Kindle

Five Stars

Reviewed in the United States on September 10, 2017

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Bioinformatic Data skills ...but aware this is a book for bioinformaticians but not for wet lab scientists

2 people found this helpful

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Top reviews from other countries

Elmira Ahmedova

Awesome guide to best practices in bioinformatics and coding in general

Reviewed in the United Kingdom on February 27, 2021

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I bought this book to get a feel for what exactly is bioinformatics as I aspire to get into this area (I have a science degree and am working as a Data Engineer following bootcamp training - to get computational skills and experience) an to my opinion it does give a decent reality check - it is about reproducibility, project folder structure, a lot of shell scripting, becoming familiar with Linux etc (you can tell I didn't get further than Chapter 4 yet!). Anyway, great read, super happy with the purchase!

One person found this helpful

Maurice

Most likely has all you need to get started

Reviewed in the United Kingdom on November 6, 2021

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A perfect blend of theoretical and practical synopsis

One person found this helpful

Amazon Customer

Well written, has little use for comp sci people

Reviewed in Canada on December 1, 2017

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I think this book will be useful for those who are not familiar with Linux and basic programming.
However, the book doesn't have that much info on Bioinformatics. 70% of the book is about Linux command line, git source control and very basic R. So if you are a comp sci or a programmer then chances that you know all this stuff are pretty high.
The actual bioinformatics read starts at the end of the book.
I was hoping to see at least some info on de novo assembly, sequence alignment, NGS data processing, Galaxy and BioPython.
If you are a tech savvy then I recommend: Bioinformatics: A Practical Handbook Of Next Generation Sequencing And Its Applications
This book has a good listing and a brief explanation of all necessary tools to conduct a full analysis.

4 people found this helpful

Andrew Dalby

Excellent first half, the second half is good if you do next generation sequencing, if you don't then don't bother reading it.

Reviewed in the United Kingdom on July 7, 2016

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This book starts off really well and the emphasis on reproducibility and systematic research is very important. The chapters on setting up a project, Git and Unix Data tools are all excellent. The chapter on R is also very good and it has some great tips for bioinformatics analysis and creating workflows. It is when the book focuses on ranged data that it all goes a bit off track. While this is important to the author and important in carrying out certain types of bioinformatics analysis (next generation sequencing work), this is not all that there is to bioinformatics. In fact as a bioinformatician who has been working in the field for over 20 years this is a pretty small part of the likely analysis you might have to do. This is made worse by not putting these ranged data files and in particular the aligned files into context. Where do they comes from? What are you using them for? What questions do you want to ask? From this point on the book is less complete and just focuses on the authors particular experience. For sequence analysis there is much more than SNPs. I worked mostly with proteins and these are not covered at all.

So if you are doing next generation sequence analysis and if you want to know good practice then this is a great book, but if you want to get a complete range of bioinformatics data skills then this is going to be one of the many books that you need. The first half is definitely worth reading for ALL bioinformaticians but the second half needs a firmer direction.

7 people found this helpful

Audald Lloret i Villas

Nice first step in Bioinformatics

Reviewed in Spain on November 22, 2015

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Great for beginners, looking forward to have some spare time and go deeper. My biological background is taken into account and the explanation is easy to follow.

One person found this helpful

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Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools 1st Edition

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