Streamlining large-scale genomic data management: Insights from the UK Biobank whole-genome sequencing data

Biobank-scale whole-genome sequencing (WGS) studies are increasingly pivotal in unraveling the genetic bases of diverse health outcomes. However, managing and analyzing these datasets' sheer volume and complexity presents significant challenges. We highlight the annotated genomic data structure (aGDS) format, substantially reducing the WGS data file size while enabling seamless integration of genomic and functional information for comprehensive WGS analyses. The aGDS format yielded 23 chromosome-specific files for the UK Biobank 500k WGS dataset, occupying only 1.10 tebibytes of storage. We develop the vcf2agds toolkit that streamlines the conversion of WGS data from VCF to aGDS format. Additionally, the STAARpipeline equipped with the aGDS files enabled scalable, comprehensive, and functionally informed WGS analysis, facilitating the detection of common and rare coding and noncoding phenotype-genotype associations. Overall, the vcf2agds toolkit and STAARpipeline provide a streamlined solution that facilitates efficient data management and analysis of biobank-scale WGS data across hundreds of thousands of samples.

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Publication Details

Journal
Cell Genomics
Published
2025-09-23
DOI
https://doi.org/10.1016/j.xgen.2025.101009
Citations
5
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
9.09

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article

Streamlining large-scale genomic data management: Insights from the UK Biobank whole-genome sequencing data

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5 citations
Cell Genomics
Genomics and Rare Diseases
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article

Streamlining large-scale genomic data management: Insights from the UK Biobank whole-genome sequencing data

Yushu Huang, Andrew R. Wood, Xihong Lin, Manrui Zhang, Robin N. Beaumont, Xihao Li, Gareth Hawkes, Wenyuan Li, Zilin Li, Xiaoyu Li, Yuxin Yuan, Michael N. Weedon
article en
5 citations

Abstract

Biobank-scale whole-genome sequencing (WGS) studies are increasingly pivotal in unraveling the genetic bases of diverse health outcomes. However, managing and analyzing these datasets' sheer volume and complexity presents significant challenges. We highlight the annotated genomic data structure (aGDS) format, substantially reducing the WGS data file size while enabling seamless integration of genomic and functional information for comprehensive WGS analyses. The aGDS format yielded 23 chromosome-specific files for the UK Biobank 500k WGS dataset, occupying only 1.10 tebibytes of storage. We develop the vcf2agds toolkit that streamlines the conversion of WGS data from VCF to aGDS format. Additionally, the STAARpipeline equipped with the aGDS files enabled scalable, comprehensive, and functionally informed WGS analysis, facilitating the detection of common and rare coding and noncoding phenotype-genotype associations. Overall, the vcf2agds toolkit and STAARpipeline provide a streamlined solution that facilitates efficient data management and analysis of biobank-scale WGS data across hundreds of thousands of samples.

Cell GenomicsVol. 5(12)
University of North Carolina at Chapel Hill (US), Harvard University (US), Northeast Normal University (CN), University of Exeter (GB), Second Affiliated Hospital of Zhejiang University (CN), Tsinghua University (CN)
UK Research and Innovation, National Institute for Health and Care Research, Department of Health and Social Care, Université de Genève, National Institutes of Health, Medical Research Council
Openalex Percentile: Top 2%
Genomics and Rare Diseases
9.09
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