Statistical modeling in case-control real-time RT-PCR assays, for identification of differentially expressed genes in schizophrenia
Statistical modeling in case-control real-time RT-PCR assays, for identification of differentially expressed genes in schizophrenia
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DOI：
10.1093/biostatistics/kxi045
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发表时间：
2006-01-01
期刊：
影响因子：
2.1
通讯作者：
Jazin, E
中科院分区：
文献类型：
--
作者：
Sundberg, R;Castensson, A;Jazin, E
讨论了病例对照实时逆转录 - 聚合酶链反应（RT - PCR）实验中的实验设计、统计建模和统计推断等方面。背景是对先前被认为与精神分裂症相关的基因进行研究得到的mRNA表达数据。实时RT - PCR可用于大量个体样本。然而，当个体数量多于每板的孔数时，就需要不完全设计。构建了一个基本的多变量（针对几个基因联合）协方差随机效应分析模型，该模型包含个体之间和个体内部的异质性。发现利用参照基因形成额外的回归变量是非常有效的。由于个体之间和个体内部的回归通常不同，首先对个体内重复样本进行平均是很重要的。这对板效应的影响有重要意义。还讨论的主题包括对显著的平均疾病效应的检验、差异共调控以及识别仅在部分病例亚组中受影响的基因的困难。
Aspects of experimental design, statistical modeling, and statistical inference in case-control real-time reverse transcription-polymerase chain reaction (RT-PCR) assays are discussed. The background is mRNA expression data from an investigation of genes previously suggested to be schizophrenia related. Real-time RT-PCR allows large samples of individuals. However, with more individuals than positions per plate, incomplete designs are required. A basic multivariate (for several genes jointly) random-effects analysis of covariance model, incorporating heterogeneity both between and within individuals, is formulated. The use of reference genes to form additional regressors is found to be highly efficient. Because regressions between and within individuals are usually different, it is important first to average over the intraindividual replicates. This has consequences for the influence of plate effects. Topics also discussed are testing for a significant mean disease effect, differential coregulation, and the difficulty of identifying genes affected in only a subgroup of cases.