Genomics In The Cloud Using Docker Gatk And Wdl In Terra
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Genomics Analysis with Spark, Docker and Clouds
Genomics researchers today are faced with an ever-increasing amount of data to analyze, and yet they have a difficult time leveraging modern frameworks and technologies (like Spark and cloud infrastructure) to efficiently and accurately analyze their data. This practical guide provides the guidance these researchers need. With this book, you'll learn how to combine algorithms designed for genomics with the leading tool for big data--Spark--and the ascendant paradigm of working in the cloud with Docker.
Genomics in the Cloud
Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytes-or 52.4 million gigabytes-of genomic data, and they're turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Brian O'Connor of the UC Santa Cruz Genomics Institute and Geraldine Van der Auwera, longtime custodian of the GATK user community, guide you through the process. You'll learn by working with real data and genomics algorithms from the field. This book takes you through: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK Three major GATK best practices for variant discovery pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra.
Genomics in the Cloud
Author: Geraldine A. Van der Auwera
language: en
Publisher: O'Reilly Media
Release Date: 2020-04-02
Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytesâ??or over 50 million gigabytesâ??of genomic data, and theyâ??re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian Oâ??Connor of the UC Santa Cruz Genomics Institute, guide you through the process. Youâ??ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra