| Title: | Streamlining large-scale genomic data management: Insights from the UK Biobank whole-genome sequencing data |
| Journal: | Cell Genomics |
| Published: | 18 Sep 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40972583/ |
| DOI: | https://doi.org/10.1016/j.xgen.2025.101009 |
| URL: | https://www.cell.com/cell-genomics/pdf/S2666-979X(25)00265-4.pdf |
Publication 19470
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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.</p>
10 Keywords
- Biological Specimen Banks
- Data Management
- Databases, Genetic
- Genome, Human
- Genomics
- Humans
- Software
- UK Biobank
- United Kingdom
- Whole Genome Sequencing
12 Authors
- Xihao Li
- Andrew R. Wood
- Yuxin Yuan
- Manrui Zhang
- Yushu Huang
- Gareth Hawkes
- Robin N. Beaumont
- Michael N. Weedon
- Wenyuan Li
- Xiaoyu Li
- Xihong Lin
- Zilin Li
5 Applications
| Application ID | Title |
|---|---|
| 9072 | The Genetics of anthropometric traits ? Height, weight, BMI and waist circumference |
| 52008 | Development of statistical methods to discover novel genetic associations, explain underlying biological mechanisms, and develop risk prediction models across varied complex diseases. |
| 91486 | Social, lifestyle, and biological risk factors of age-related diseases and mortality |
| 103356 | Understanding the role of rare and common genetic variation in human phenotypes |
| 211447 | Statistical methods and scalable cloud-based toolset for integrative analysis of biobank-scale sequencing studies and biobanks for complex diseases |
Enabling scientific discoveries that improve human health