Bioinformatics Data Skills by Oreilly——学习生信的入门好书

翻阅《生信宝典》公众号，偶然看到推荐的两本生信入门好书，分享给大家：

1. 《Bioinformatics Data Skills - - Reproducible.and.Robust.Research.with.Open.Source.Tools》链接:》链接: 接: https://pan.baidu.com/s/1c2g0MPU 密码: 密码: v2c9
2. 《Bioinformatics with Python Cookbook》链接: 接: https://pan.baidu.com/s/1dF0H52x 密码: 密码: a7e4

自己看了其中比较初级版本的《Bioinformatics Data Skills》的第一章（简介部分），全书500多页，虽然是全英文，但是通俗易懂，适合对Linux、Python（文本处理语言）等有一些基本了解的新手学习。

若对两者不太了解，本书又推荐了一些有用的书籍，如：
用于Python学习的：Bioinformatics Programming
Using Python by Mitchell L. Model (O’Reilly, 2009), Learning Python, 5th Edition,by Mark Lutz (O’Reilly, 2013), and Python in a Nutshell, 2nd, by Alex Martelli(O’Reilly, 2006)
用于了解Unix命令的： Practical Computing for Biologists
by Steven Haddock and Casey Dunn (Sinauer, 2010) or UNIX and Perl to the Rescue by Keith Bradnam and Ian Korf (Cambridge University Press, 2012).
关于正则表达式的运用：Introducing Regular Expressions by Michael Fitzgerald (O’Reilly) ；http://regex101.com and http://www.debug‐gex.com to write,test and debug regular expressions.

Supplementary Material on GitHub
本书的附加材料在GitHub上可以获得（Chapter 5 中介绍）。

Computing Resources and Setup
若是Mac环境，作者推荐使用Homebrew帮助你进行软件的安装。有条件的最好是在Linux或Unix环境下，进行测试

Organization of This Book
共分为三大部分：
Part I, containing one chapter on ideology;
Part II, which covers the basics of getting started with a bioinformatics project;
Part III, which covers bioinformatics data skills.
Chapter2. trivial topic, organized project, markdown
Chapter3. Unix
Chapter4. increase productivity when working with remote machines.
Chapter5. Git
Chapter6. download data, validate integrity
Part III 第七章之后是实战
Chapter7. Unix data tools, Unix pipelines
Chapter8. R language
Chapter9. genomic data
Chapter10. sequence data FASTA, FASTQ
Chapter11. SAM,BAM,Samtools,variant calling
Chapter12. data-processing scripts and pipelines(Bash scriptin, find and xargs)
Chapter13. Tabix, SQL, GWAS
Chapter14. further develop

We have a web page for this book, where we list errata, examples, and any additional information. You can access this page at http://bit.ly/Bio-DS.