| Description |
1 online resource |
| Contents |
Copyright; Table of Contents; Preface; The Approach of This Book; Why This Book Focuses on Sequencing Data; Audience; The Difficulty Level of Bioinformatics Data Skills; Assumptions This Book Makes; Supplementary Material on GitHub; Computing Resources and Setup; Organization of This Book; Code Conventions; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Part I. Ideology: Data Skills for Robust and Reproducible Bioinformatics; Chapter 1. How to Learn Bioinformatics; Why Bioinformatics? Biology's Growing Data |
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Learning Data Skills to Learn BioinformaticsNew Challenges for Reproducible and Robust Research; Reproducible Research; Robust Research and the Golden Rule of Bioinformatics; Adopting Robust and Reproducible Practices Will Make Your Life Easier, Too; Recommendations for Robust Research; Pay Attention to Experimental Design; Write Code for Humans, Write Data for Computers; Let Your Computer Do the Work For You; Make Assertions and Be Loud, in Code and in Your Methods; Test Code, or Better Yet, Let Code Test Code; Use Existing Libraries Whenever Possible; Treat Data as Read-Only |
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Spend Time Developing Frequently Used Scripts into ToolsLet Data Prove That It's High Quality; Recommendations for Reproducible Research; Release Your Code and Data; Document Everything; Make Figures and Statistics the Results of Scripts; Use Code as Documentation; Continually Improving Your Bioinformatics Data Skills; Part II. Prerequisites: Essential Skills for Getting Started with a Bioinformatics Project; Chapter 2. Setting Up and Managing a Bioinformatics Project; Project Directories and Directory Structures; Project Documentation |
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Use Directories to Divide Up Your Project into SubprojectsOrganizing Data to Automate File Processing Tasks; Markdown for Project Notebooks; Markdown Formatting Basics; Using Pandoc to Render Markdown to HTML; Chapter 3. Remedial Unix Shell; Why Do We Use Unix in Bioinformatics? Modularity and the Unix Philosophy; Working with Streams and Redirection; Redirecting Standard Out to a File; Redirecting Standard Error; Using Standard Input Redirection; The Almighty Unix Pipe: Speed and Beauty in One; Pipes in Action: Creating Simple Programs with Grep and Pipes; Combining Pipes and Redirection |
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Even More Redirection: A tee in Your PipeManaging and Interacting with Processes; Background Processes; Killing Processes; Exit Status: How to Programmatically Tell Whether Your Command Worked; Command Substitution; Chapter 4. Working with Remote Machines; Connecting to Remote Machines with SSH; Quick Authentication with SSH Keys; Maintaining Long-Running Jobs with nohup and tmux; nohup; Working with Remote Machines Through Tmux; Installing and Configuring Tmux; Creating, Detaching, and Attaching Tmux Sessions; Working with Tmux Windows; Chapter 5. Git for Scientists |
| Summary |
Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, you'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 life'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, you'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 |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Online resource; title from PDF title page (Ebsco, viewed July 9, 2015) |
| Subject |
Bioinformatics.
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Biology.
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Computational Biology
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Database Management Systems
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Biology
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Electronic Data Processing
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Information Science
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biology.
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SCIENCE -- Life Sciences -- Biochemistry.
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Biology.
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Bioinformatics.
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| Form |
Electronic book
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| LC no. |
2015458838 |
| ISBN |
9781449367510 |
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1449367518 |
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9781449367503 |
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144936750X |
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9781449367480 |
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1449367488 |
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