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Genomics In The Cloud Using Docker Gatk And Wdl In Terra Geraldine A Van Der Auwera Brian D Oconnor

  • SKU: BELL-10901246
Genomics In The Cloud Using Docker Gatk And Wdl In Terra Geraldine A Van Der Auwera Brian D Oconnor
$ 31.00 $ 45.00 (-31%)

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Genomics In The Cloud Using Docker Gatk And Wdl In Terra Geraldine A Van Der Auwera Brian D Oconnor instant download after payment.

Publisher: O'Reilly Media, Inc.
File Extension: EPUB
File size: 27.51 MB
Pages: 496
Author: Geraldine A. Van der Auwera; Brian D. O'Connor
ISBN: 9781491975145, 1491975148
Language: English
Year: 2020

Product desciption

Genomics In The Cloud Using Docker Gatk And Wdl In Terra Geraldine A Van Der Auwera Brian D Oconnor by Geraldine A. Van Der Auwera; Brian D. O'connor 9781491975145, 1491975148 instant download after payment.

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

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