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.
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Dr. Geraldine A. Van der Auwera is the Director of Outreach and Communication for the Data Sciences Platform (DSP) at the Broad Institute of MIT and Harvard. As part of her outreach role, she serves as an educator and advocate for researchers who use DSP software and services including GATK, the Broad's industry-leading toolkit for variant discovery analysis; the Cromwell/WDL workflow management system; and Terra.bio, a cloud-based analysis platform that integrates computational resources, methods repository and data management in a user-friendly environment. Van der Auwera was originally trained as a microbiologist, earning her Ph.D. in Biological Engineering from the Université catholique de Louvain (UCL) in Belgium in 2007, then surviving a 4-year postdoctoral stint at Harvard Medical School. She joined the Broad Institute in 2012 to become Benevolent Dictator For Life of the GATK user community, leaving behind the bench and pipette work forever.
Dr. Brian O'Connor is the Director of the Computational Genomics Platform at the University of California Santa Cruz (UCSC) Genomics Institute. There, he focuses on the development and deployment of large-scale, cloud-based systems for analyzing genomic data. These include the NHGRI AnVIL and NHLBI Bio Data Catalyst platforms as well as the Dockstore site for workflow and tool sharing. Brian is active in standards efforts and is the cochair of the Global Alliance for Genomics and Health Cloud Work Stream where he works on API standards for cloud interoperability. Brian joined UCSC from the Ontario Institute for Cancer Research where his previous projects included leading the technical implementation of worldwide, cloud-based analysis systems for the PanCancer Analysis of Whole Genomes project, creating the Dockstore, and managing a successful rebuild of the International Cancer Genome Consortium's Data Portal.
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Paperback. Zustand: New. 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 backgroundBasic cloud computing operationsGetting started with GATK, plus three major GATK Best Practices pipelinesAutomating analysis with scripted workflows using WDL and CromwellScaling up workflow execution in the cloud, including parallelization and cost optimizationInteractive analysis in the cloud using Jupyter notebooksSecure collaboration and computational reproducibility using Terra. Artikel-Nr. LU-9781491975190
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Paperback. Zustand: New. 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 backgroundBasic cloud computing operationsGetting started with GATK, plus three major GATK Best Practices pipelinesAutomating analysis with scripted workflows using WDL and CromwellScaling up workflow execution in the cloud, including parallelization and cost optimizationInteractive analysis in the cloud using Jupyter notebooksSecure collaboration and computational reproducibility using Terra. Artikel-Nr. LU-9781491975190
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Paperback. Zustand: New. 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 backgroundBasic cloud computing operationsGetting started with GATK, plus three major GATK Best Practices pipelinesAutomating analysis with scripted workflows using WDL and CromwellScaling up workflow execution in the cloud, including parallelization and cost optimizationInteractive analysis in the cloud using Jupyter notebooksSecure collaboration and computational reproducibility using Terra. Artikel-Nr. LU-9781491975190
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Taschenbuch. Zustand: Neu. Neuware - Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytesor over 50 million gigabytesof 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 not Elektronisches Buch- Secure collaboration and computational reproducibility using Terra. Artikel-Nr. 9781491975190
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