PGSFusion streamlines polygenic score construction and epidemiological applications in biobank-scale cohorts.

IF 10.4 1区 生物学 Q1 GENETICS & HEREDITY
Sheng Yang, Xiangyu Ye, Xiaolong Ji, Zhenghui Li, Min Tian, Peng Huang, Chen Cao
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引用次数: 0

Abstract

Background: The polygenic score (PGS) is an estimate of an individual's genetic susceptibility to a specific complex trait and has been instrumental to the development of precision medicine. As an increasing number of genome-wide association studies (GWAS) have emerged, numerous sophisticated statistical and computational methods have been developed to facilitate the PGS construction. However, both the complex statistical estimation procedure and the various data formats of summary statistics and reference panel make the PGS calculation challenging and not easily accessible to researchers with limited statistical and computational backgrounds.

Results: Here, we propose PGSFusion, a webserver designed to carry out PGS construction for targeting variety of analytic requirements while requiring minimal prior computational knowledge. Implemented with well-established web development technologies, PGSFusion streamlines the construction of PGS using 17 PGS methods in four categories: 11 single-trait, one multiple-trait, two annotation-based and three cross-ancestry based methods. In addition, PGSFusion also utilizes UK Biobank data to provide two kinds of in-depth analyses for 201 complex traits: i) prediction performance evaluation to display the consistency between PGS and specific traits and the effect size of PGS in different genetic risk groups; ii) joint effect analysis to investigate the interaction between PGS and covariates, as well as the effect size of covariates in different genetic subgroups. PGSFusion benchmarks the prediction performances for different methods in one summary statistics. PGSFusion automatically identifies the required parameters in different data formats of uploaded GWAS summary statistics files, provides a selection of suitable methods, and outputs calculated PGSs and their corresponding epidemiological results. Finally, we showcase three case studies in different application scenarios, highlighting its versatility and values to researchers.

Conclusions: Overall, PGSFusion presents an easy-to-use, effective, and extensible platform for PGS construction, promoting the accessibility and utility of PGS for researchers in the field of precision medicine. PGSFusion is freely available at http://www.pgsfusion.net/ .

PGSFusion简化了多基因评分的构建和在生物库规模队列中的流行病学应用。
背景:多基因评分(PGS)是对个体对特定复杂性状的遗传易感性的估计,对精准医学的发展起着重要作用。随着越来越多的全基因组关联研究(GWAS)的出现,许多复杂的统计和计算方法已经发展起来,以促进PGS的构建。然而,复杂的统计估计过程以及汇总统计和参考面板的各种数据格式使得PGS计算具有挑战性,并且对于具有有限统计和计算背景的研究人员来说不容易实现。结果:在这里,我们提出了PGSFusion,这是一个web服务器,旨在针对各种分析需求进行PGS构建,同时需要最少的先验计算知识。PGSFusion采用成熟的web开发技术,使用17种PGS方法简化了PGS的构建,分为4类:11种单性状方法、1种多性状方法、2种基于注释的方法和3种基于交叉祖先的方法。此外,PGSFusion还利用UK Biobank数据对201个复杂性状进行了两种深度分析:1)预测性能评价,显示PGS与特定性状的一致性以及PGS在不同遗传风险群体中的效应大小;ii)联合效应分析,研究PGS与协变量之间的相互作用,以及不同遗传亚群协变量的效应大小。PGSFusion在一个汇总统计中对不同方法的预测性能进行基准测试。PGSFusion自动识别上传的GWAS汇总统计文件中不同数据格式的所需参数,选择合适的方法,输出计算出的PGSs及其相应的流行病学结果。最后,我们展示了三个不同应用场景下的案例研究,突出了它的通用性和对研究者的价值。结论:总体而言,PGSFusion提供了一个易于使用、有效且可扩展的PGS构建平台,促进了PGS在精准医学领域的可及性和实用性。PGSFusion可以在http://www.pgsfusion.net/免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Genome Medicine
Genome Medicine GENETICS & HEREDITY-
CiteScore
20.80
自引率
0.80%
发文量
128
审稿时长
6-12 weeks
期刊介绍: Genome Medicine is an open access journal that publishes outstanding research applying genetics, genomics, and multi-omics to understand, diagnose, and treat disease. Bridging basic science and clinical research, it covers areas such as cancer genomics, immuno-oncology, immunogenomics, infectious disease, microbiome, neurogenomics, systems medicine, clinical genomics, gene therapies, precision medicine, and clinical trials. The journal publishes original research, methods, software, and reviews to serve authors and promote broad interest and importance in the field.
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