A Statistical Approach in Using cDNA Array Analysis to Determine Modest Changes in Gene Expression in Several Brain Regions after Neurotoxic Insult
A Statistical Approach in Using cDNA Array Analysis to Determine Modest Changes in Gene Expression in Several Brain Regions after Neurotoxic Insult
复制标题
使用 cDNA 阵列分析确定神经毒性损伤后几个脑区基因表达适度变化的统计方法
DOI：
10.1111/j.1749-6632.2003.tb07546.x
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发表时间：
2003
影响因子：
5.2
通讯作者：
J. Bowyer
中科院分区：
文献类型：
--
作者：
R. Delongchamp;A. Harris;J. Bowyer
摘要：在轻度至中度神经毒性暴露于化合物（如取代安非他明）后，或在更严重的神经毒性暴露后数周的时间点，预期基因表达的适度变化可能为3倍或更少。当许多基因的表达变化小于两倍时，运行几对阵列并使用统计分析来确定哪些基因真正发生了变化是至关重要的。这限制了必须进行耗时的RT-PCR任务以验证表达水平变化的基因数量。我们在这里描述的方法，统计确定哪些基因被表达高于背景水平。这些方法用于比较纹状体，顶叶皮质，杏仁后外侧核和黑质脑区域之间的表达差异，所有这些区域在其基因表达谱上都有显着差异。在这些比较中，有可能区分数百个基因之间的差异，并可管理地估计错误发现率。苯丙胺治疗对杏仁后外侧核基因表达的影响也进行了评估。表达数据表明许多基因已经改变，但在这种情况下，将受影响的基因与假阳性分开更加困难。最佳列表有50个基因，其中32%预计是假阳性。
Abstract: Modest changes in gene expression of three‐fold or less might be expected after mild to moderate neurotoxic exposure to classes of compounds, such as the substituted amphetamines, or at time points that are weeks after more severe neurotoxic exposures. When many genes appear to change expression by less than two‐fold, it is crucial to run several pairs of arrays and use statistical analysis to determine which genes are really changing. This limits the number of genes that have to undergo the time consuming task of performing RT‐PCR to validate change in expression levels. We describe here methods for statistically determining which genes are being expressed above background levels. These methods are used to compare expression differences among the striatum, parietal cortex, posterior lateral amygdaloid nucleus, and substantia nigra brain regions, all of which differ significantly in their gene expression profiles. In these comparisons, it was possible to distinguish differences among hundreds of genes with manageable estimated false discovery rates. The effect of amphetamine treatment on gene expression in posterior lateral amygdaloid nucleus was also evaluated. The expression data indicate that many genes have changed, but in this case it is more difficult to separate affected genes from false positives. The optimum list has 50 genes, of which 32% are expected to be false positives.
DOI：
10.1073/pnas.97.18.9834
发表时间：
2000-08-29
影响因子：
11.1
作者：
Lee, MLT;Kuo, FC;Sklar, J
通讯作者：
Sklar, J