Yohhan Kumarasinghe, Jacob Williams, Yuxin Yuan, Wenbo Wang, Julie-Alexia Dias, Haoyu Zhang, Zilin Li, Xihao Li
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引用次数: 0
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. MetaSTAARlite provides a scalable and resource-efficient summary statistics-based pipeline for powerful, functionally informed rare-variant meta-analysis of biobank-scale sequencing data.
生物库规模的测序研究已经能够分析导致复杂性状的罕见变异。在这里,我们介绍MetaSTAARlite,一个可扩展和资源高效的基于汇总统计的管道,用于编码和非编码基因组的功能信息罕见变异荟萃分析,绕过了使用多个生物库的个人水平数据进行汇总分析的数据共享限制。使用UK Biobank和All of Us Research Program的测序数据,我们证明MetaSTAARlite的计算时间、内存和存储需求与样本量呈线性增长,同时产生的结果与汇集分析的结果高度一致。