| Title: | MetaSTAARlite: an all-in-one tool for biobank-scale whole-genome sequencing meta-analysis |
| Journal: | Nature Computational Science |
| Published: | 3 Jun 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42236576/ |
| DOI: | https://doi.org/10.1038/s43588-026-00995-x |
| URL: | https://www.medrxiv.org/content/medrxiv/early/2025/06/06/2025.06.05.25328973.full.pdf |
Publication 19840
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Abstract
Biobank-scale sequencing studies have enabled the analysis of rare variants contributing to complex traits. Here we introduce MetaSTAARlite, a scalable and resource-efficient summary statistics-based pipeline for functionally informed rare-variant meta-analysis in both the coding and noncoding genome, bypassing the data-sharing restrictions of pooled analysis using individual-level data across multiple biobanks. Using the sequencing data of the UK Biobank and the All of Us Research Program, we demonstrate that MetaSTAARlite's computation time, memory and storage requirements scale linearly with sample size, while producing results highly concordant with those of a pooled analysis.</p>
8 Authors
- Yohhan Kumarasinghe
- Jacob Williams
- Yuxin Yuan
- Wenbo Wang
- Julie-Alexia Dias
- Haoyu Zhang
- Zilin Li
- Xihao Li
3 Applications
| Application ID | Title |
|---|---|
| 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 |
| 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