Set-Valued Analysis for Genome-Wide Association Studies of Complex Diseases

被引：0
|
作者：
Bi Wenjian [1 ]
Zhao Yanlong [1 ]
Liu Chenxing [2 ]
Yue Weihua [2 ]
机构：
[1] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
[2] Peking Univ, Hosp 6, Beijing 100191, Peoples R China
来源：
2013 32ND CHINESE CONTROL CONFERENCE (CCC) | 2013年
关键词：
Complex disease; Genome-wide association study; System identification with quantized observations; Iteration algorithm; Phenotype inference; LOGISTIC-REGRESSION; BIPOLAR DISORDER; SUSCEPTIBILITY; SCHIZOPHRENIA; LOCUS; CANDIDATE; EPISTASIS; DIAGNOSIS; VARIANTS; CHINESE;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes set-value analysis for genome-wide association studies (GWAS) of complex diseases. A FIR model is established to describe the relationship between single nucleotide polymorphism (SNP) data and complex disease phenotype. An iteration algorithm based on maximum likelihood estimation is introduced to identify the parameter of model. A numerical simulation example is constructed to demonstrate the convergence of iteration algorithm. This method can be used to GWAS of schizophrenia and the error rate of phenotype inference is shown to be under 25%. The last part briefly summarizes this article and looks forward to the related further work.
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收藏
页码：8262 / 8267
页数：6
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