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A cloud-based training module for efficient de novo transcriptome assembly using Nextflow and Google cloud.
Seaman, Ryan P; Campbell, Ross; Doe, Valena; Yosufzai, Zelaikha; Graber, Joel H.
Afiliación
  • Seaman RP; MDI Biological Laboratory, 159 Old Bar Harbor Road, Bar Harbor, ME 04609, USA.
  • Campbell R; Health Data and AI, 4301 Fairfax Dr, Unit 210, Deloitte Consulting LLP, Arlington, VA 22203, USA.
  • Doe V; Google Cloud, Google, 1900 Reston Metro Plaza, Reston, VA 20190, USA.
  • Yosufzai Z; Health Data and AI, 4301 Fairfax Dr, Unit 210, Deloitte Consulting LLP, Arlington, VA 22203, USA.
  • Graber JH; MDI Biological Laboratory, 159 Old Bar Harbor Road, Bar Harbor, ME 04609, USA.
Brief Bioinform ; 25(4)2024 May 23.
Article en En | MEDLINE | ID: mdl-38941113
ABSTRACT
This study describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" (https//github.com/NIGMS/NIGMS-Sandbox). The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on de novo transcriptome assembly using Nextflow in an interactive format that uses appropriate cloud resources for data access and analysis. Cloud computing is a powerful new means by which biomedical researchers can access resources and capacity that were previously either unattainable or prohibitively expensive. To take advantage of these resources, however, the biomedical research community needs new skills and knowledge. We present here a cloud-based training module, developed in conjunction with Google Cloud, Deloitte Consulting, and the NIH STRIDES Program, that uses the biological problem of de novo transcriptome assembly to demonstrate and teach the concepts of computational workflows (using Nextflow) and cost- and resource-efficient use of Cloud services (using Google Cloud Platform). Our work highlights the reduced necessity of on-site computing resources and the accessibility of cloud-based infrastructure for bioinformatics applications.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Transcriptoma / Nube Computacional Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Transcriptoma / Nube Computacional Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos