1000基因组计划
生物
插补(统计学)
索引
基因组
计算生物学
人口
基因组学
数据质量
数据科学
遗传学
进化生物学
数据挖掘
计算机科学
缺少数据
基因
公制(单位)
单核苷酸多态性
运营管理
人口学
机器学习
社会学
基因型
经济
作者
Zan Koenig,Mary T. Yohannes,Lethukuthula L. Nkambule,Xuefang Zhao,Julia K. Goodrich,Heesu Ally Kim,Michael W. Wilson,Grace Tiao,Stephanie P. Hao,Nareh Sahakian,Katherine R. Chao,Mark A. Walker,Yunfei Lyu,Heidi L. Rehm,Benjamin M. Neale,Michael E. Talkowski,Mark J. Daly,Harrison Brand,Konrad J. Karczewski,Elizabeth G. Atkinson,Alicia R. Martin
出处
期刊:Genome Research
[Cold Spring Harbor Laboratory]
日期:2024-05-01
卷期号:34 (5): 796-809
被引量:14
标识
DOI:10.1101/gr.278378.123
摘要
Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.
科研通智能强力驱动
Strongly Powered by AbleSci AI