Last updated:
Author(s):
Yohhan Kumarasinghe, Jacob Williams, Yuxin Yuan, Wenbo Wang, Julie-Alexia Dias, Haoyu Zhang, Zilin Li, Xihao Li
Publish date:
3 June 2026
Journal:
Nature Computational Science
PubMed ID:
42236576

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.

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