Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks.
Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks.
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单倍型估计和整个基因组推出的准确性会影响复杂的生物库中的复杂性状分析。
DOI：
10.1038/s42003-023-04477-y
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发表时间：
2023-01-26
影响因子：
5.9
通讯作者：
中科院分区：
文献类型：
--
作者：
研究联盟、生物样本库和个人基因组学公司的样本招募跨越数年，需要使用不同的技术分批进行基因分型。由于基因分型芯片上的标记内容各不相同，整合此类数据集并非易事，其对单倍型估计（定相）和全基因组插补（复杂性状分析的必要步骤）的影响仍然未被充分评估。使用由 130,438 名个体组成的 iPSYCH 数据集，在不同的阵列上分两个阶段进行基因分型，我们评估了多种定相方法和数据集成协议的定相和插补性能。虽然定相精度因方法和数据集成协议的选择而异，但插补精度主要因数据集成协议而异。我们证明了非欧洲血统样本中插补准确性的衰减，突显了研究不同人群的复杂性状所面临的挑战。最后，插补错误可能会使关联测试产生偏差，降低多基因评分的预测效用。精心优化的数据集成策略提高了复杂生物库中复杂性状分析的准确性和可重复性。使用跨多种方法和数据集成协议的 iPSYCH 联盟数据对分相和插补性能进行分析，为设计构建下一代生物库或进行生物库规模分析的工作流程提供了有用的框架。
Sample recruitment for research consortia, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can bias association tests, reduce predictive utility of polygenic scores. Carefully optimized data integration strategies enhance accuracy and replicability of complex trait analyses in complex biobanks. An analysis of phasing and imputation performances using iPSYCH consortium data across multiple methods and data integration protocols provides a useful framework in designing workflows to construct next-generation biobanks or conduct biobank-scale analyses.
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影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者：
Marchini J
基因发现和多基因预测，从基因组全基因组协会的教育程度研究中，有110万个人。
影响因子：
30.8
作者：
Lee JJ;Wedow R;Okbay A;Kong E;Maghzian O;Zacher M;Nguyen-Viet TA;Bowers P;Sidorenko J;Karlsson Linnér R;Fontana MA;Kundu T;Lee C;Li H;Li R;Royer R;Timshel PN;Walters RK;Willoughby EA;Yengo L;23andMe Research Team;COGENT (Cognitive Genomics Consortium);Social Science Genetic Association Consortium;Alver M;Bao Y;Clark DW;Day FR;Furlotte NA;Joshi PK;Kemper KE;Kleinman A;Langenberg C;Mägi R;Trampush JW;Verma SS;Wu Y;Lam M;Zhao JH;Zheng Z;Boardman JD;Campbell H;Freese J;Harris KM;Hayward C;Herd P;Kumari M;Lencz T;Luan J;Malhotra AK;Metspalu A;Milani L;Ong KK;Perry JRB;Porteous DJ;Ritchie MD;Smart MC;Smith BH;Tung JY;Wareham NJ;Wilson JF;Beauchamp JP;Conley DC;Esko T;Lehrer SF;Magnusson PKE;Oskarsson S;Pers TH;Robinson MR;Thom K;Watson C;Chabris CF;Meyer MN;Laibson DI;Yang J;Johannesson M;Koellinger PD;Turley P;Visscher PM;Benjamin DJ;Cesarini D
通讯作者：
Cesarini D
影响因子：
12.3
作者：
Chen SF;Dias R;Evans D;Salfati EL;Liu S;Wineinger NE;Torkamani A
通讯作者：
Torkamani A
影响因子：
30.8
作者：
Das, Sayantan;Forer, Lukas;Schoenherr, Sebastian;Sidore, Carlo;Locke, Adam E.;Kwong, Alan;Vrieze, Scott I.;Chew, Emily Y.;Levy, Shawn;McGue, Matt;Schlessinger, David;Stambolian, Dwight;Loh, Po-Ru;Iacono, William G.;Swaroop, Anand;Scott, Laura J.;Cucca, Francesco;Kronenberg, Florian;Boehnke, Michael;Abecasis, Goncalo R.;Fuchsberger, Christian
通讯作者：
Fuchsberger, Christian
影响因子：
30.8
作者：
Loh, Po-Ru;Danecek, Petr;Palamara, Pier Francesco;Fuchsberger, Christian;Reshef, Yakir A.;Finucane, Hilary K.;Schoenherr, Sebastian;Forer, Lukas;McCarthy, Shane;Abecasis, Goncalo R.;Durbin, Richard;Price, Alkes L.
通讯作者：
Price, Alkes L.