locStra: Fast analysis of regional/global stratification in whole-genome sequencing studies.
locStra: Fast analysis of regional/global stratification in whole-genome sequencing studies.
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LOCSTRA：全基因组测序研究中区域/全球分层的快速分析。
DOI：
10.1002/gepi.22356
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发表时间：
2021-03
影响因子：
2.1
通讯作者：
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
中科院分区：
文献类型：
--
作者：
Hahn G;Lutz SM;Hecker J;Prokopenko D;Cho MH;Silverman EK;Weiss ST;Lange C;NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
locStra是一个用于全基因组测序（WGS）研究中区域和全球群体分层分析的r包，其中区域分层是指基因组上特定区域的位点定义的亚结构。利用遗传协方差矩阵、基因组关系矩阵和未加权/加权遗传Jaccard相似性矩阵对种群亚结构进行评价。采用滑动窗口方法，根据用户自定义的窗口大小和度量，例如区域特征向量与全局特征向量之间的相关性，将区域相似矩阵与全局相似矩阵进行比较。给出了一种指定窗口大小的算法。由于实现充分利用了稀疏矩阵代数，并且是用c++编写的，因此分析效率很高。即使在单个核心上，对于实际的研究规模（几千个受试者，每个受试者几百万个罕见变异），所有区域相似性矩阵的全基因组计算的运行时间通常不超过一个小时，这使得对整个基因组的区域分层进行前所未有的调查成为可能。该软件包应用于三个WGS研究，说明了整个基因组区域亚结构的不同模式及其对关联测试的有益影响。
locStra is an R-package for the analysis of regional and global population stratification in whole-genome sequencing (WGS) studies, where regional stratification refers to the substructure defined by the loci in a particular region on the genome. Population substructure can be assessed based on the genetic covariance matrix, the genomic relationship matrix, and the unweighted/ weighted genetic Jaccard similarity matrix. Using a sliding window approach, the regional similarity matrices are compared with the global ones, based on user-defined window sizes and metrics, for example, the correlation between regional and global eigenvectors. An algorithm for the specification of the window size is provided. As the implementation fully exploits sparse matrix algebra and is written in C++, the analysis is highly efficient. Even on single cores, for realistic study sizes (several thousand subjects, several million rare variants per subject), the runtime for the genome-wide computation of all regional similarity matrices does typically not exceed one hour, enabling an unprecedented investigation of regional stratification across the entire genome. The package is applied to three WGS studies, illustrating the varying patterns of regional substructure across the genome and its beneficial effects on association testing.
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影响因子：
2.9
作者：
Lutz SM;Cho MH;Young K;Hersh CP;Castaldi PJ;McDonald ML;Regan E;Mattheisen M;DeMeo DL;Parker M;Foreman M;Make BJ;Jensen RL;Casaburi R;Lomas DA;Bhatt SP;Bakke P;Gulsvik A;Crapo JD;Beaty TH;Laird NM;Lange C;Hokanson JE;Silverman EK;ECLIPSE Investigators;COPDGene Investigators
通讯作者：
COPDGene Investigators
DOI：
10.1073/pnas.0812824106
发表时间：
2009-03-10
影响因子：
11.1
作者：
Kryukov, Gregory V.;Shpunt, Alexander;Sunyaev, Shamil R.
通讯作者：
Sunyaev, Shamil R.
DOI：
10.1126/science.1217283
发表时间：
2012-05-11
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Keinan A;Clark AG
通讯作者：
Clark AG
影响因子：
30.8
作者：
通讯作者：
--
影响因子：
14.2
作者：
Hunninghake, Gary M.;Soto-Quiros, Manuel E.;Celedon, Juan C.
通讯作者：
Celedon, Juan C.