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Programs for calculating the statistical powers of detecting susceptibility genes in case–control studies based on multistage designs

机译:基于多阶段设计的病例对照研究中检测易感基因检测的统计能力的程序

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摘要

>Motivation: A two-stage association study is the most commonly used method among multistage designs to efficiently identify disease susceptibility genes. Recently, some SNP studies have utilized more than two stages to detect disease genes. However, there are few available programs for calculating statistical powers and positive predictive values (PPVs) of arbitrary n-stage designs.>Results: We developed programs for a multistage case–control association study using R language. In our programs, input parameters include numbers of samples and candidate loci, genome-wide false positive rate and proportions of samples and loci to be selected at the k-th stage (k=1,…, n). The programs output statistical powers, PPVs and numbers of typings in arbitrary n-stage designs. The programs can contribute to prior simulations under various conditions in planning a genome-wide association study.>Availability: The R programs are freely available for academic users and can be downloaded from >Contact: >Supplementary information: are available at Bioinformatics online.
机译:>动机:两阶段关联研究是多阶段设计中最常用的有效识别疾病易感基因的方法。最近,一些SNP研究已经利用了两个以上的阶段来检测疾病基因。但是,几乎没有可用的程序来计算任意n阶段设计的统计功效和正预测值(PPV)。>结果:我们使用R语言开发了用于多阶段病例-对照关联研究的程序。在我们的程序中,输入参数包括样本和候选基因座的数量,全基因组假阳性率以及在第k个阶段中要选择的样本和基因座的比例(k = 1,…,n)。程序在任意n阶段设计中输出统计功效,PPV和类型数。这些程序可在计划全基因组关联研究的各种条件下促进先前的模拟。>可用性: R程序可免费供学术用户使用,并可从>联系方式下载: >补充信息:可在线访问生物信息学。

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