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Active OTHER RESEARCH-RELATED NIH (US)

Supplement: Enhancing Community Contributions to Bioconductor With Build System Containerization and a GPU for Testing

$2.28M USD

Funder NATIONAL HUMAN GENOME RESEARCH INSTITUTE
Recipient Organization Dana-Farber Cancer Inst
Country United States
Start Date Sep 06, 2023
End Date Feb 28, 2026
Duration 906 days
Number of Grantees 2
Roles Co-Investigator; Principal Investigator
Data Source NIH (US)
Grant ID 10838736
Grant Description

PROJECT SUMMARY/ABSTRACT "Bioconductor: An Open-Source, Open-Development Computing Resource for Genomics" is the parent grant of this application for supplemental funds. Bioconductor is an open source, open development ecosystem of software and data for the analysis and comprehension of genome- scale experiments. The system is primarily rooted in the R language but has extensive

interoperability capabilities and incorporates tools developed in numerous other languages. Bioconductor resources are requested at scientific and industrial sites throughout the world, with an outflow from Bioonductor's cloud distribution systems of approximately 1TB of software and data per day. The system provides infrastructure for genome representation and

representation of variants, genomic sequences and gene models for numerous model organisms, analytical software for many array and sequencing platforms, and annotation and experiment archives, all checked for consistency and portability on a daily basis. This request for supplemental funds addresses engineering requirements of the build and distribution

system, which has had its present structure for over ten years, and adds support for graphical processing units in the build and test system. Our plan includes work on containerization and upscaling of the build and check system, and enhancement of the methods of recording resource use and adverse events in ecosystem build processes. In essence, the proposed

work will allow the Bioconductor project to more fully embrace an "Infrastructure as Code" discipline to simplify redeployment and rescaling in response to throughput requirements, and to improve automatic discovery and reporting of system problems. Because the requirements of the genomic data science community are continually diversifying in terms of complexity and

volume of data being generated, and the number of hardware platforms in use is likewise growing, the work proposed cannot be accomplished under the initial funding plan.

All Grantees

Dana-Farber Cancer Inst

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