On the association analysis of genome-sequencing data: A spatial clustering approach for partitioning the entire genome into nonoverlapping windows.
On the association analysis of genome-sequencing data: A spatial clustering approach for partitioning the entire genome into nonoverlapping windows.
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DOI：
10.1002/gepi.22040
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发表时间：
2017-05
影响因子：
2.1
通讯作者：
Lange C
中科院分区：
文献类型：
--
作者：
Loehlein Fier H;Prokopenko D;Hecker J;Cho MH;Silverman EK;Weiss ST;Tanzi RE;Lange C
针对全基因组测序（WGS）研究的关联分析，提出了一种高效快速的空间聚类算法。与WGS数据的现有分析方法相比，其通过沿着变体的固定大小的滑动或连续窗口来定义测试区域，将附近变体有意义地分组到连续区域中具有以下优点：与滑动窗口方法相比，测试区域的数量可能更小。与连续的固定窗口方法相比，我们的方法可能会将附近的变体分组在一起。鉴于现有的生物学证据表明，疾病相关的突变往往在物理上聚集在特定区域沿着染色体，附近定位的变异的有意义的群体的鉴定，从而可能导致关联分析的潜在功率增益。我们的算法定义连续的基因组区域的基础上的物理位置的变体，假设一个非齐次泊松过程和组在一起附近的变体。由于参数是局部估计的，该算法考虑了染色体上沿着不同的变异密度，并将变异局部最优划分为连续区域。一个R-实现的算法。我们讨论了我们的算法的理论进展相比，现有的，基于窗口的方法，并显示我们引入的算法在模拟研究和应用程序阿尔茨海默氏病WGS数据的性能和优势。我们的分析确定了ITGB 3基因中的一个区域，该区域可能含有阿尔茨海默病的疾病易感性位点。ITGB 3的基于区域的关联信号在独立的数据集中复制，并实现了形式上的全基因组意义。
For the association analysis of whole-genome sequencing (WGS) studies, we propose an efficient and fast spatial-clustering algorithm. Compared to existing analysis approaches for WGS data, that define the tested regions either by sliding or consecutive windows of fixed sizes along variants, a meaningful grouping of nearby variants into consecutive regions has the advantage that, compared to sliding window approaches, the number of tested regions is likely to be smaller. In comparison to consecutive, fixed-window approaches, our approach is likely to group nearby variants together. Given existing biological evidence that disease-associated mutations tend to physically cluster in specific regions along the chromosome, the identification of meaningful groups of nearby located variants could thus lead to a potential power gain for association analysis. Our algorithm defines consecutive genomic regions based on the physical positions of the variants, assuming an inhomogeneous Poisson process and groups together nearby variants. As parameters are estimated locally, the algorithm takes the differing variant density along the chromosome into account and provides locally optimal partitioning of variants into consecutive regions. An R-implementation of the algorithm is provided. We discuss the theoretical advances of our algorithm compared to existing, window-based approaches and show the performance and advantage of our introduced algorithm in a simulation study and by an application to Alzheimer’s disease WGS data. Our analysis identifies a region in the ITGB3 gene that potentially harbors disease susceptibility loci for Alzheimer’s disease. The region-based association signal of ITGB3 replicates in an independent data set and achieves formally genome-wide significance.
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影响因子：
2.1
作者：
Wang, Haizhou;Song, Mingzhou
通讯作者：
Song, Mingzhou
影响因子：
64.8
作者：
Sudmant PH;Rausch T;Gardner EJ;Handsaker RE;Abyzov A;Huddleston J;Zhang Y;Ye K;Jun G;Fritz MH;Konkel MK;Malhotra A;Stütz AM;Shi X;Casale FP;Chen J;Hormozdiari F;Dayama G;Chen K;Malig M;Chaisson MJP;Walter K;Meiers S;Kashin S;Garrison E;Auton A;Lam HYK;Mu XJ;Alkan C;Antaki D;Bae T;Cerveira E;Chines P;Chong Z;Clarke L;Dal E;Ding L;Emery S;Fan X;Gujral M;Kahveci F;Kidd JM;Kong Y;Lameijer EW;McCarthy S;Flicek P;Gibbs RA;Marth G;Mason CE;Menelaou A;Muzny DM;Nelson BJ;Noor A;Parrish NF;Pendleton M;Quitadamo A;Raeder B;Schadt EE;Romanovitch M;Schlattl A;Sebra R;Shabalin AA;Untergasser A;Walker JA;Wang M;Yu F;Zhang C;Zhang J;Zheng-Bradley X;Zhou W;Zichner T;Sebat J;Batzer MA;McCarroll SA;1000 Genomes Project Consortium;Mills RE;Gerstein MB;Bashir A;Stegle O;Devine SE;Lee C;Eichler EE;Korbel JO
通讯作者：
Korbel JO
影响因子：
9.8
作者：
He, Zongxiao;O'Roak, Brian J.;Leal, Suzanne M.
通讯作者：
Leal, Suzanne M.
影响因子：
6.3
作者：
Stellos, Konstantinos;Panagiota, Victoria;Laske, Christoph
通讯作者：
Laske, Christoph
影响因子：
3.3
作者：
EVANS, IS
通讯作者：
EVANS, IS