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 over 50 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 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.

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 O'Connor of the UC Santa Cruz Genomics Institute, guide you through the process. You'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