pwrBRIDGE: a user-friendly web application for power and sample size estimation in batch-confounded microarray studies with dependent samples.

IF 0.9 4区 数学 Q3 Mathematics
Qing Xia, Jeffrey A Thompson, Devin C Koestler
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引用次数: 0

Abstract

Batch effect Reduction of mIcroarray data with Dependent samples usinG Empirical Bayes (BRIDGE) is a recently developed statistical method to address the issue of batch effect correction in batch-confounded microarray studies with dependent samples. The key component of the BRIDGE methodology is the use of samples run as technical replicates in two or more batches, "bridging samples", to inform batch effect correction/attenuation. While previously published results indicate a relationship between the number of bridging samples, M, and the statistical power of downstream statistical testing on the batch-corrected data, there is of yet no formal statistical framework or user-friendly software, for estimating M to achieve a specific statistical power for hypothesis tests conducted on the batch-corrected data. To fill this gap, we developed pwrBRIDGE, a simulation-based approach to estimate the bridging sample size, M, in batch-confounded longitudinal microarray studies. To illustrate the use of pwrBRIDGE, we consider a hypothetical, longitudinal batch-confounded study whose goal is to identify Alzheimer's disease (AD) progression-associated genes from amnestic mild cognitive impairment (aMCI) to AD in human blood after a 5-year follow-up. pwrBRIDGE helps researchers design and plan batch-confounded microarray studies with dependent samples to avoid over- or under-powered studies.

pwrBRIDGE:一个用户友好的web应用程序,用于在依赖样本的批量混杂微阵列研究中估计功率和样本量。
使用经验贝叶斯(BRIDGE)减少依赖样本的微阵列数据的批量效应是最近发展起来的一种统计方法,用于解决具有依赖样本的批量混杂微阵列研究中的批量效应校正问题。BRIDGE方法的关键组成部分是使用在两个或多个批次中作为技术复制运行的样品,“桥接样品”,以通知批次效果校正/衰减。虽然先前发表的结果表明桥接样本的数量M与批量校正数据的下游统计检验的统计能力之间存在关系,但目前还没有正式的统计框架或用户友好的软件来估计M,以实现对批量校正数据进行假设检验的特定统计能力。为了填补这一空白,我们开发了pwrBRIDGE,这是一种基于模拟的方法,用于估计批量混淆纵向微阵列研究中的桥接样本量M。为了说明pwrBRIDGE的使用,我们考虑了一项假设的纵向批量混淆研究,其目标是在5年随访后确定人类血液中从遗忘性轻度认知障碍(aMCI)到AD的阿尔茨海默病(AD)进展相关基因。pwrBRIDGE帮助研究人员设计和计划与依赖样本的批量混淆微阵列研究,以避免过度或不足的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.20
自引率
11.10%
发文量
8
审稿时长
6-12 weeks
期刊介绍: Statistical Applications in Genetics and Molecular Biology seeks to publish significant research on the application of statistical ideas to problems arising from computational biology. The focus of the papers should be on the relevant statistical issues but should contain a succinct description of the relevant biological problem being considered. The range of topics is wide and will include topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies. Both original research and review articles will be warmly received.
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