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Comparison of dimension reduction-based logistic regression models for case-control genome-wide association study:principal components analysis vs.partial least squares 被引量:2
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作者 Honggang Yi Hongmei Wo +9 位作者 Yang Zhao Ruyang Zhang Junchen Dai Guangfu Jin Hongxia Ma Tangchun Wu Zhibin Hu Dongxin Lin Hongbing Shen Feng Chen 《The Journal of Biomedical Research》 CAS CSCD 2015年第4期298-307,共10页
With recent advances in biotechnology, genome-wide association study (GWAS) has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistica... With recent advances in biotechnology, genome-wide association study (GWAS) has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistical strategy is traditional logistical regression (LR) based on single-locus analysis. However, such a single-locus analysis leads to the well-known multiplicity problem, with a risk of inflating type I error and reducing power. Dimension reduction-based techniques, such as principal component-based logistic regression (PC-LR), partial least squares-based logistic regression (PLS-LR), have recently gained much attention in the analysis of high dimensional genomic data. However, the perfor- mance of these methods is still not clear, especially in GWAS. We conducted simulations and real data application to compare the type I error and power of PC-LR, PLS-LR and LR applicable to GWAS within a defined single nucleotide polymorphism (SNP) set region. We found that PC-LR and PLS can reasonably control type I error under null hypothesis. On contrast, LR, which is corrected by Bonferroni method, was more conserved in all simulation settings. In particular, we found that PC-LR and PLS-LR had comparable power and they both outperformed LR, especially when the causal SNP was in high linkage disequilibrium with genotyped ones and with a small effective size in simulation. Based on SNP set analysis, we applied all three methods to analyze non-small cell lung cancer GWAS data. 展开更多
关键词 principal components analysis partial least squares-based logistic regression genome-wide association study type I error POWER
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The transfer line design for the HEPS project 被引量:4
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作者 Yuanyuan Wei Yuemei Peng +1 位作者 Gang Xu Yuanyuan Guo 《Radiation Detection Technology and Methods》 CSCD 2020年第4期440-447,共8页
Purpose The high energy photon source(HEPS),a 6-GeV synchrotron radiation facility with ultralow emittance,is under construction in China.Three transfer lines are designed for HEPS.One low-energy transfer line is used... Purpose The high energy photon source(HEPS),a 6-GeV synchrotron radiation facility with ultralow emittance,is under construction in China.Three transfer lines are designed for HEPS.One low-energy transfer line is used to deliver the 500 MeV beam provided by the linac to the booster.Two high-energy transfer lines are used to connect the booster and the storage ring to realize beam accumulation in the booster at 6 GeV.Method The design of the transfer lines is closely related to the layout and optics design of the storage ring,booster and linac.Based on the physics design of the storage ring,booster and linac,the design of the transfer lines has been adjusted.Results and conclusion In this paper,the considerations and design of the latest lattice of transfer lines are described.The design satisfies the requirements of the high efficiency transmission and injection. 展开更多
关键词 HEPS Transfer lines OPTICS error study
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