Identifying rarer genetic variants for common complex diseases: diseased versus neutral discovery panels.
Identifying rarer genetic variants for common complex diseases: diseased versus neutral discovery panels.
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DOI：
10.1111/j.1469-1809.2008.00483.x
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发表时间：
2009-01
影响因子：
1.9
通讯作者：
Camp NJ
中科院分区：
文献类型：
--
作者：
Curtin K;Iles MM;Camp NJ
遗传关联研究鉴定疾病易感性等位基因的能力从根本上依赖于所研究的变异。标准的方法是确定一组标记SNP（tSNP），通过利用局部相关结构来捕获感兴趣区域中的大部分基因组变异。通常，tSNP选自中性发现组，即跨区域全面基因分型的个体集合。我们研究了发现面板设计的关联研究中使用真实模拟的序列数据的tSNP性能的影响。我们发现，24个测序的“中性”个体的发现组（类似于NIEHS或HapMap ENCODE数据）足以选择功效良好的tSNP来鉴定常见的易感性等位基因。对于不太常见的等位基因（0.01-0.05频率），我们发现这种大小的中性组是不够的，特别是如果在tSNP选择之前去除低频变体;使用患病个体组发现上级tSNP。只有大的中性面板（200个个体）匹配患病面板的性能，选择良好的功率tSNP检测常见和罕见的等位基因。1000个基因组计划的倡议可能会提供更大的中性面板，以确定在关联研究中罕见的易感性等位基因。在此期间，我们的研究结果表明，研究人员可以通过对患病个体进行测序以进行tSNP选择来提高检测此类等位基因的能力。
The power of genetic association studies to identify disease susceptibility alleles fundamentally relies on the variants studied. The standard approach is to determine a set of tagging-SNPs (tSNPs) that capture the majority of genomic variation in regions of interest by exploiting local correlation structures. Typically, tSNPs are selected from neutral discovery panels, collections of individuals comprehensively genotyped across a region. We investigated the implications of discovery panel design on tSNP performance in association studies using realistically-simulated sequence data. We found that discovery panels of 24 sequenced ‘neutral’ individuals (similar to NIEHS or HapMap ENCODE data) were sufficient to select well-powered tSNPs to identify common susceptibility alleles. For less common alleles (0.01–0.05 frequency) we found neutral panels of this size inadequate, particularly if low-frequency variants were removed prior to tSNP selection; superior tSNPs were found using panels of diseased individuals. Only large neutral panels (200 individuals) matched diseased panel performance in selecting well-powered tSNPs to detect both common and rarer alleles. The 1000 Genomes Project initiative may provide larger neutral panels necessary to identify rarer susceptibility alleles in association studies. In the interim, our results suggest investigators can boost power to detect such alleles by sequencing diseased individuals for tSNP selection.
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影响因子：
64.8
作者：
Frazer, Kelly A.;Ballinger, Dennis G.;Cox, David R.;Hinds, David A.;Stuve, Laura L.;Gibbs, Richard A.;Belmont, John W.;Boudreau, Andrew;Hardenbol, Paul;Leal, Suzanne M.;Pasternak, Shiran;Wheeler, David A.;Willis, Thomas D.;Yu, Fuli;Yang, Huanming;Zeng, Changqing;Gao, Yang;Hu, Haoran;Hu, Weitao;Li, Chaohua;Lin, Wei;Liu, Siqi;Pan, Hao;Tang, Xiaoli;Wang, Jian;Wang, Wei;Yu, Jun;Zhang, Bo;Zhang, Qingrun;Zhao, Hongbin;Zhao, Hui;Zhou, Jun;Gabriel, Stacey B.;Barry, Rachel;Blumenstiel, Brendan;Camargo, Amy;Defelice, Matthew;Faggart, Maura;Goyette, Mary;Gupta, Supriya;Moore, Jamie;Nguyen, Huy;Onofrio, Robert C.;Parkin, Melissa;Roy, Jessica;Stahl, Erich;Winchester, Ellen;Ziaugra, Liuda;Altshuler, David;Shen, Yan;Yao, Zhijian;Huang, Wei;Chu, Xun;He, Yungang;Jin, Li;Liu, Yangfan;Shen, Yayun;Sun, Weiwei;Wang, Haifeng;Wang, Yi;Wang, Ying;Xiong, Xiaoyan;Xu, Liang;Waye, Mary M. Y.;Tsui, Stephen K. W.;Wong, J. Tze-Fei;Galver, Luana M.;Fan, Jian-Bing;Gunderson, Kevin;Murray, Sarah S.;Oliphant, Arnold R.;Chee, Mark S.;Montpetit, Alexandre;Chagnon, Fanny;Ferretti, Vincent;Leboeuf, Martin;Olivier, Jean-Franccois;Phillips, Michael S.;Roumy, Stephanie;Sallee, Clementine;Verner, Andrei;Hudson, Thomas J.;Kwok, Pui-Yan;Cai, Dongmei;Koboldt, Daniel C.;Miller, Raymond D.;Pawlikowska, Ludmila;Taillon-Miller, Patricia;Xiao, Ming;Tsui, Lap-Chee;Mak, William;Song, You Qiang;Tam, Paul K. H.;Nakamura, Yusuke;Kawaguchi, Takahisa;Kitamoto, Takuya;Morizono, Takashi;Nagashima, Atsushi;Ohnishi, Yozo;Sekine, Akihiro;Tanaka, Toshihiro;Tsunoda, Tatsuhiko;Deloukas, Panos;Bird, Christine P.;Delgado, Marcos;Dermitzakis, Emmanouil T.;Gwilliam, Rhian;Hunt, Sarah;Morrison, Jonathan;Powell, Don;Stranger, Barbara E.;Whittaker, Pamela;Bentley, David R.;Daly, Mark J.;de Bakker, Paul I. W.;Barrett, Jeff;Chretien, Yves R.;Maller, Julian;McCarroll, Steve;Patterson, Nick;Pe'er, Itsik;Price, Alkes;Purcell, Shaun;Richter, Daniel J.;Sabeti, Pardis;Saxena, Richa;Schaffner, Stephen F.;Sham, Pak C.;Varilly, Patrick;Altshuler, David;Stein, Lincoln D.;Krishnan, Lalitha;Smith, Albert Vernon;Tello-Ruiz, Marcela K.;Thorisson, Gudmundur A.;Chakravarti, Aravinda;Chen, Peter E.;Cutler, David J.;Kashuk, Carl S.;Lin, Shin;Abecasis, Goncalo R.;Guan, Weihua;Li, Yun;Munro, Heather M.;Qin, Zhaohui Steve;Thomas, Daryl J.;McVean, Gilean;Auton, Adam;Bottolo, Leonardo;Cardin, Niall;Eyheramendy, Susana;Freeman, Colin;Marchini, Jonathan;Myers, Simon;Spencer, Chris;Stephens, Matthew;Donnelly, Peter;Cardon, Lon R.;Clarke, Geraldine;Evans, David M.;Morris, Andrew P.;Weir, Bruce S.;Tsunoda, Tatsuhiko;Johnson, Todd A.;Mullikin, James C.;Sherry, Stephen T.;Feolo, Michael;Skol, Andrew
通讯作者：
Skol, Andrew
影响因子：
2.9
作者：
Klein, Robert J.
通讯作者：
Klein, Robert J.
影响因子：
9.8
作者：
Gorlov, Ivan P.;Gorlova, Olga Y.;Amos, Christopher I.
通讯作者：
Amos, Christopher I.
影响因子：
64.8
作者：
Gibbs, RA;Belmont, JW;Tanaka, T
通讯作者：
Tanaka, T
影响因子：
30.8
作者：
Phillips, MS;Lawrence, R;Cardon, LR
通讯作者：
Cardon, LR