Learning React: Modern Patterns for Developing React Apps,2nd Edition

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. 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 Foreword Preface 1.Introduction 2.Genomics in a Nutshell: A Primer for Newcomers to the Field 3.Computing Technology Basics for Life Scientists 4.First Steps in the Cloud 5.First Steps with GATK 6.GATK Best Practices for Germline Short Variant Discovery 7.GATK Best Practices for Somatic Variant Discovery 8.Automating Analysis Execution with Workflows 9.Deciphering Real Genomics Workflows 10.Running Single Workflows at Scale with Pipelines APl 11.Running Many Workflows Conveniently in Terra 12.Interactive Analysis in Jupyter Notebook 13.Assembling Your Own Workspace in Terra 14.Making a Fully Reproducible Paper Glossary Index