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DYNATE:通过聚合树中嵌入的多重检验来定位罕见变异关联区域。

DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree.

机构信息

Novartis Pharmaceuticals Corporation, Basel, Switzerland.

AstraZeneca, Cambridge, UK.

出版信息

Genet Epidemiol. 2024 Feb;48(1):42-55. doi: 10.1002/gepi.22542. Epub 2023 Nov 28.

DOI:10.1002/gepi.22542
PMID:38014869
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10842871/
Abstract

Rare-variants (RVs) genetic association studies enable researchers to uncover the variation in phenotypic traits left unexplained by common variation. Traditional single-variant analysis lacks power; thus, researchers have developed various methods to aggregate the effects of RVs across genomic regions to study their collective impact. Some existing methods utilize a static delineation of genomic regions, often resulting in suboptimal effect aggregation, as neutral subregions within the test region will result in an attenuation of signal. Other methods use varying windows to search for signals but often result in long regions containing many neutral RVs. To pinpoint short genomic regions enriched for disease-associated RVs, we developed a novel method, DYNamic Aggregation TEsting (DYNATE). DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones and performs multiple testing for disease associations with a controlled weighted false discovery rate. DYNATE's main advantage lies in its strong ability to identify short genomic regions highly enriched for disease-associated RVs. Extensive numerical simulations demonstrate the superior performance of DYNATE under various scenarios compared with existing methods. We applied DYNATE to an amyotrophic lateral sclerosis study and identified a new gene, EPG5, harboring possibly pathogenic mutations.

摘要

罕见变异(RVs)的遗传关联研究使研究人员能够发现常见变异无法解释的表型特征的变化。传统的单变异分析缺乏效力;因此,研究人员开发了各种方法来聚合基因组区域中 RVs 的效应,以研究它们的集体影响。一些现有的方法利用基因组区域的静态划分,这通常导致效应聚合效果不佳,因为测试区域内的中性亚区会导致信号衰减。其他方法使用不同的窗口来搜索信号,但通常会导致包含许多中性 RVs 的长区域。为了精确定位富含与疾病相关的 RVs 的短基因组区域,我们开发了一种新方法,即动态聚合测试(DYNATE)。DYNATE 以动态和分层的方式将较小的基因组区域聚合到较大的区域中,并对疾病相关性进行多次测试,以控制加权错误发现率。DYNATE 的主要优势在于其能够识别富含与疾病相关的 RVs 的短基因组区域的强大能力。广泛的数值模拟表明,与现有方法相比,DYNATE 在各种情况下的表现都更为优越。我们将 DYNATE 应用于肌萎缩侧索硬化症研究中,鉴定出一个新基因 EPG5,该基因可能含有致病性突变。

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本文引用的文献

1
TEAM: A MULTIPLE TESTING ALGORITHM ON THE AGGREGATION TREE FOR FLOW CYTOMETRY ANALYSIS.TEAM:一种用于流式细胞术分析的聚合树上的多重测试算法。
Ann Appl Stat. 2023 Mar;17(1):621-640. doi: 10.1214/22-aoas1645. Epub 2023 Jan 24.
2
A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.一种用于检测大规模全基因组测序研究中非编码稀有变异关联的框架。
Nat Methods. 2022 Dec;19(12):1599-1611. doi: 10.1038/s41592-022-01640-x. Epub 2022 Oct 27.
3
Simultaneous Detection of Signal Regions Using Quadratic Scan Statistics With Applications to Whole Genome Association Studies.
使用二次扫描统计量同时检测信号区域及其在全基因组关联研究中的应用
J Am Stat Assoc. 2022;117(538):823-834. doi: 10.1080/01621459.2020.1822849. Epub 2020 Nov 12.
4
Insights on autophagosome-lysosome tethering from structural and biochemical characterization of human autophagy factor EPG5.从人自噬因子 EPG5 的结构和生化特征看自噬小体-溶酶体连接
Commun Biol. 2021 Mar 5;4(1):291. doi: 10.1038/s42003-021-01830-x.
5
Cauchy combination test: a powerful test with analytic -value calculation under arbitrary dependency structures.柯西组合检验:一种在任意相依结构下具有解析值计算功能的强大检验。
J Am Stat Assoc. 2020;115(529):393-402. doi: 10.1080/01621459.2018.1554485. Epub 2019 Apr 25.
6
The exhaustive genomic scan approach, with an application to rare-variant association analysis.穷尽基因组扫描方法及其在罕见变异关联分析中的应用。
Eur J Hum Genet. 2020 Sep;28(9):1283-1291. doi: 10.1038/s41431-020-0639-3. Epub 2020 May 15.
7
Quantitative phenotype scan statistic (QPSS) reveals rare variant associations with Alzheimer's disease endophenotypes.定量表型扫描统计(QPSS)揭示了与阿尔茨海默病内表型相关的罕见变异。
BMC Med Genet. 2020 May 15;21(1):106. doi: 10.1186/s12881-020-01046-6.
8
Rare-variant collapsing analyses for complex traits: guidelines and applications.复杂性状的罕见变异合并分析:指南与应用。
Nat Rev Genet. 2019 Dec;20(12):747-759. doi: 10.1038/s41576-019-0177-4. Epub 2019 Oct 11.
9
A genome-wide scan statistic framework for whole-genome sequence data analysis.全基因组序列数据分析的全基因组扫描统计框架。
Nat Commun. 2019 Jul 9;10(1):3018. doi: 10.1038/s41467-019-11023-0.
10
Dynamic Scan Procedure for Detecting Rare-Variant Association Regions in Whole-Genome Sequencing Studies.全基因组测序研究中稀有变异关联区域的动态扫描程序。
Am J Hum Genet. 2019 May 2;104(5):802-814. doi: 10.1016/j.ajhg.2019.03.002. Epub 2019 Apr 12.