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

2015-02-01 20:55:55|  分类: 好书推荐 |  标签: |举报 |字号 订阅

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Bioinformatics Data Skills:Reproducible and Robust Research with Open Source Tools - 喜欢吃桃子 - wangyufeng的博客
 

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 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


  1. Chapter 1Ideology: Data Skills, Robust and Reproducible Bioinformatics

  2. Chapter 2Prerequisites: Setting up a Project, Working with Unix, Version Control, and Data

  3. Chapter 3Remedial Unix Shell

  4. Chapter 4Working with Remote Machines

  5. Chapter 5Git for Scientists

  6. Chapter 6Bioinformatics Data

  7. Chapter 7Unix Data Tools

  8. Chapter 8A Rapid Introduction to the R Language

  9. Chapter 9Working with Range Data

  10. Chapter 10Working with Sequence Data

  11. Chapter 11Working with Alignment Data

  12. Chapter 12Automating Tasks and Writing Bioinformatics Pipelines

  13. Chapter 13Working with Databases

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