title: SNP set association analysis for genome-wide association studies.
abstract: Genome-wide association study (GWAS) is a promising approach for identifying common genetic variants of the diseases on the basis of millions of single nucleotide polymorphisms (SNPs). In order to avoid low power caused by overmuch correction for multiple comparisons in single locus association study, some methods have been proposed by grouping SNPs together into a SNP set based on genomic features, then testing the joint effect of the SNP set. We compare the performances of principal component analysis (PCA), supervised principal component analysis (SPCA), kernel principal component analysis (KPCA), and sliced inverse regression (SIR). Simulated SNP sets are generated under scenarios of 0, 1 and ≥ 2 causal SNPs model. Our simulation results show that all of these methods can control the type I error at the nominal significance level. SPCA is always more powerful than the other methods at different settings of linkage disequilibrium structures and minor allele frequency of the simulated datasets. We also apply these four methods to a real GWAS of non-small cell lung cancer (NSCLC) in Han Chinese population.
authors: Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China.
authors: Min
authors: M
authors: Cai
authors: Hui
authors: H
authors: Dai
authors: Yongyong
authors: Y
authors: Qiu
authors: Yang
authors: Y
authors: Zhao
authors: Ruyang
authors: R
authors: Zhang
authors: Minjie
authors: M
authors: Chu
authors: Juncheng
authors: J
authors: Dai
authors: Zhibin
authors: Z
authors: Hu
authors: Hongbing
authors: H
authors: Shen
authors: Feng
authors: F
authors: Chen
mesh_terms: D000483:Alleles; D044466:Asian People; D002289:Carcinoma, Non-Small-Cell Lung / Q000208:ethnology / Q000235:genetics*; D003198:Computer Simulation; D004268:DNA-Binding Proteins / Q000235:genetics*; D005787:Gene Frequency; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data*; D006801:Humans; D015810:Linkage Disequilibrium; D008175:Lung Neoplasms / Q000208:ethnology / Q000235:genetics*; D008565:Membrane Proteins / Q000235:genetics*; D008957:Models, Genetic; D009363:Neoplasm Proteins / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D025341:Principal Component Analysis / Q000379:methods; D012107:Research Design; D012984:Software; D000076105:X-ray Repair Cross Complementing Protein 1
chemical_list: C422445:CLPTM1L protein, human; D004268:DNA-Binding Proteins; D008565:Membrane Proteins; D009363:Neoplasm Proteins; D000076105:X-ray Repair Cross Complementing Protein 1
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