首页> 外文会议>IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology >Comparing multiple testing correction methods between two softwares for single nucleotide polymorphisms association analyses: Using OPRDI and diastolic blood pressure in methadone maintenance patients as an example
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Comparing multiple testing correction methods between two softwares for single nucleotide polymorphisms association analyses: Using OPRDI and diastolic blood pressure in methadone maintenance patients as an example

机译:对单核苷酸多态性关联分析的两个软件之间的多种测试校正方法分析:在美沙酮维持患者中使用OPRDI和舒张压为例

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Multi-testing correction methods are usually applied in more than one single nucleotide polymorphisms (SNPs) of association analyses to determine the significance of results in the face of testing multiple hypotheses. One of the statistical methods applied in these analyses is called false discovery rate (FDR) procedure. In this study, we compared the FDR theories behind the statistical software of Statistical Analysis Software (SAS) and Golden Helix using a database obtained from a methadone maintenance treatment cohort in Taiwan. The association analyses were performed between the delta opioid receptor (OPRD1) of seven SNPs from rs2236861 to rs760588, or four SNPs from rs2236861 to rs419335, and the diastolic blood pressure (DBP) in both genotypes and allele types. In general linear model (GLM) of association analyses, SNP rs797397 had the most significant association with DBP among seven or four SNPs of both genotype (p=0.0012) and allele type (p=0.0004) using SAS and Golden Helix programs. The genotype and allele type of this SNP had 0.0039 and 0.0018 FDR, respectively after Benjamini and Hochberg (BH) procedure analyses using SAS program, and had 0.0083 and 0.0027 FDR, respectively after the positive false discovery rate (pFDR) analyses using Golden Helix program in seven SNPs. The genotype and allele type of this SNP had 0.0022 and 0.0015 FDR, respectively after BH analyses and 0.0047 and 0.0015 FDR, respectively after pFDR analyses in four SNPs. In summary, the pFDR had less significant level than BH procedure in the most significant GLM associations SNP in both genotypes and allele types at seven and four numbers of SNPs. The FDR values were the same in both BH and pFDR multiple corrections in the allele type of four SNPs. The BH procedure in SAS provided a more consistent FDR in both genotype and allele type of multiple correction analyses despite the number of SNPs.
机译:多次测试校正方法通常以多种核苷酸多态性(SNP)应用于关联分析,以确定在测试多个假设的面前结果的重要性。应用于这些分析中的统计方法之一被称为假发现率(FDR)程序。在这项研究中,我们将统计分析软件(SAS)和Golden Helix统计软件背后的FDR理论进行了使用从台湾的美沙酮维护队列的数据库进行了比较。在从RS2236861到RS760588到RS760588的七个SNP的δ阿片类药物(OPRD1)之间进行关联分析,或来自RS2236861至RS419335的四个SNP,以及基因型和等位基因类型的舒张压(DBP)。在一般线性模型(GLM)的关联分析中,SNP RS797397使用SAS和Golden Helix程序的七种或四种基因型(P = 0.0012)和等位基因类型(P = 0.0004)中最重要的与DBP相关联。本SNP的基因型和等位基因类型分别使用SAS程序分析在Benjamini和Hochberg(BH)程序分析后,分别在使用Golden Helix计划的正虚假发现率(PFDR)分析后分别为0.0039和0.0018 fdr。在七个snps。这种SNP的基因型和等位基因类型分别在BFDR分析后分析在四个SNP中的PFDR分析后分析为0.0022和0.0015 fdr,分别为0.0047和0.0015 FDR。总之,PFDR在七个和四个SNP中的基因型和等位基因类型中最重要的GLM关联SNP中的BH程序较差。 BH和PFDR中的FDR值在等位基因类型的四个SNP中的多个校正中相同。尽管SNP的数量,SAS中的BH过程在基因型和等位基因类型的多种校正分析中提供了更一致的FDR。

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