Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.
Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.
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DOI：
10.1371/journal.pone.0193256
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发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Lee PH
中科院分区：
文献类型：
--
作者：
Zhu Z;Anttila V;Smoller JW;Lee PH
最近全基因组关联研究的进展表明，对人类复杂性状的多效性效应是普遍存在的。一些经典的和最新的荟萃分析方法被用于识别具有多效性效应的遗传基因座，但这些方法的总体性能还没有被很好地理解。在这项工作中，我们使用广泛的模拟和案例研究的GWAs数据集来调查十种Meta分析方法的功率和I类错误率。我们特别关注在多个性状的研究中经常遇到的三种情况：(1)遗传效应的广泛异质性；(2)特定性状关联的表征；(3)由于重叠样本而导致的GWA相关性膨胀。虽然统计能力在不同的研究条件下是高度可变的，但我们发现在不同的异质性下，几种方法的优势能力。特别是，当一个变量与超过一半的研究特征相关时，经典的固定效应模型表现出令人惊讶的良好表现。随着无效性状数量的增加，ASSET在竞争特异性和敏感性方面表现最好。在相反的方向效应下，CPASSOC具有一流的力量。然而，当使用CPASSOC研究重叠样本的遗传相关性状时，建议谨慎。最后，我们对尚未解决的问题和未来研究的方向进行了讨论。
Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.
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影响因子：
6.2
作者：
Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium
通讯作者：
Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium
影响因子：
28.2
作者：
Kar SP;Beesley J;Amin Al Olama A;Michailidou K;Tyrer J;Kote-Jarai Z;Lawrenson K;Lindstrom S;Ramus SJ;Thompson DJ;ABCTB Investigators;Kibel AS;Dansonka-Mieszkowska A;Michael A;Dieffenbach AK;Gentry-Maharaj A;Whittemore AS;Wolk A;Monteiro A;Peixoto A;Kierzek A;Cox A;Rudolph A;Gonzalez-Neira A;Wu AH;Lindblom A;Swerdlow A;AOCS Study Group & Australian Cancer Study (Ovarian Cancer);APCB BioResource;Ziogas A;Ekici AB;Burwinkel B;Karlan BY;Nordestgaard BG;Blomqvist C;Phelan C;McLean C;Pearce CL;Vachon C;Cybulski C;Slavov C;Stegmaier C;Maier C;Ambrosone CB;Høgdall CK;Teerlink CC;Kang D;Tessier DC;Schaid DJ;Stram DO;Cramer DW;Neal DE;Eccles D;Flesch-Janys D;Edwards DR;Wokozorczyk D;Levine DA;Yannoukakos D;Sawyer EJ;Bandera EV;Poole EM;Goode EL;Khusnutdinova E;Høgdall E;Song F;Bruinsma F;Heitz F;Modugno F;Hamdy FC;Wiklund F;Giles GG;Olsson H;Wildiers H;Ulmer HU;Pandha H;Risch HA;Darabi H;Salvesen HB;Nevanlinna H;Gronberg H;Brenner H;Brauch H;Anton-Culver H;Song H;Lim HY;McNeish I;Campbell I;Vergote I;Gronwald J;Lubiński J;Stanford JL;Benítez J;Doherty JA;Permuth JB;Chang-Claude J;Donovan JL;Dennis J;Schildkraut JM;Schleutker J;Hopper JL;Kupryjanczyk J;Park JY;Figueroa J;Clements JA;Knight JA;Peto J;Cunningham JM;Pow-Sang J;Batra J;Czene K;Lu KH;Herkommer K;Khaw KT;kConFab Investigators;Matsuo K;Muir K;Offitt K;Chen K;Moysich KB;Aittomäki K;Odunsi K;Kiemeney LA;Massuger LF;Fitzgerald LM;Cook LS;Cannon-Albright L;Hooning MJ;Pike MC;Bolla MK;Luedeke M;Teixeira MR;Goodman MT;Schmidt MK;Riggan M;Aly M;Rossing MA;Beckmann MW;Moisse M;Sanderson M;Southey MC;Jones M;Lush M;Hildebrandt MA;Hou MF;Schoemaker MJ;Garcia-Closas M;Bogdanova N;Rahman N;NBCS Investigators;Le ND;Orr N;Wentzensen N;Pashayan N;Peterlongo P;Guénel P;Brennan P;Paulo P;Webb PM;Broberg P;Fasching PA;Devilee P;Wang Q;Cai Q;Li Q;Kaneva R;Butzow R;Kopperud RK;Schmutzler RK;Stephenson RA;MacInnis RJ;Hoover RN;Winqvist R;Ness R;Milne RL;Travis RC;Benlloch S;Olson SH;McDonnell SK;Tworoger SS;Maia S;Berndt S;Lee SC;Teo SH;Thibodeau SN;Bojesen SE;Gapstur SM;Kjær SK;Pejovic T;Tammela TL;GENICA Network;PRACTICAL consortium;Dörk T;Brüning T;Wahlfors T;Key TJ;Edwards TL;Menon U;Hamann U;Mitev V;Kosma VM;Setiawan VW;Kristensen V;Arndt V;Vogel W;Zheng W;Sieh W;Blot WJ;Kluzniak W;Shu XO;Gao YT;Schumacher F;Freedman ML;Berchuck A;Dunning AM;Simard J;Haiman CA;Spurdle A;Sellers TA;Hunter DJ;Henderson BE;Kraft P;Chanock SJ;Couch FJ;Hall P;Gayther SA;Easton DF;Chenevix-Trench G;Eeles R;Pharoah PD;Lambrechts D
通讯作者：
Lambrechts D
影响因子：
16.6
作者：
Day FR;Bulik-Sullivan B;Hinds DA;Finucane HK;Murabito JM;Tung JY;Ong KK;Perry JRB
通讯作者：
Perry JRB
影响因子：
30.8
作者：
Ellinghaus D;Jostins L;Spain SL;Cortes A;Bethune J;Han B;Park YR;Raychaudhuri S;Pouget JG;Hübenthal M;Folseraas T;Wang Y;Esko T;Metspalu A;Westra HJ;Franke L;Pers TH;Weersma RK;Collij V;D'Amato M;Halfvarson J;Jensen AB;Lieb W;Degenhardt F;Forstner AJ;Hofmann A;International IBD Genetics Consortium (IIBDGC);International Genetics of Ankylosing Spondylitis Consortium (IGAS);International PSC Study Group (IPSCSG);Genetic Analysis of Psoriasis Consortium (GAPC);Psoriasis Association Genetics Extension (PAGE);Schreiber S;Mrowietz U;Juran BD;Lazaridis KN;Brunak S;Dale AM;Trembath RC;Weidinger S;Weichenthal M;Ellinghaus E;Elder JT;Barker JN;Andreassen OA;McGovern DP;Karlsen TH;Barrett JC;Parkes M;Brown MA;Franke A
通讯作者：
Franke A
影响因子：
1.8
作者：
Chen, Zhongxue;Nadarajah, Saralees
通讯作者：
Nadarajah, Saralees