Rat toxicogenomic study reveals analytical consistency across microarray platforms
Rat toxicogenomic study reveals analytical consistency across microarray platforms
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DOI：
10.1038/nbt1238
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发表时间：
2006-09-01
影响因子：
46.9
通讯作者：
Shi, Leming
中科院分区：
文献类型：
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作者：
Guo, Lei;Lobenhofer, Edward K.;Shi, Leming
为了验证和扩展微阵列质量控制（MAQC）项目的发现，使用来自用三种化学物质（马兜铃酸，riddelliine和紫草）处理的大鼠的36个RNA样本生成生物学相关的毒理基因组学数据集，每个样本与四个微阵列平台杂交。MAQC项目评估了研究中心间和跨平台比较的一致性，以及基因选择方法对使用不同参考RNA样本的差异表达基因分析数据重现性的影响。本文报告的真实世界毒理基因组学数据集显示，研究中心间和跨平台比较具有高度一致性。此外，通过倍数变化排序产生的基因列表比通过t检验P值或微阵列的显著性分析获得的基因列表更可重复。最后，通过具有非严格P值截止值的倍数变化排名生成的基因列表显示基因本体论术语和途径的一致性增加，因此可以从分析的所有平台可靠地推断化学暴露的生物学影响。
To validate and extend the findings of the MicroArray Quality Control (MAQC) project, a biologically relevant toxicogenomics data set was generated using 36 RNA samples from rats treated with three chemicals (aristolochic acid, riddelliine and comfrey) and each sample was hybridized to four microarray platforms. The MAQC project assessed concordance in intersite and cross-platform comparisons and the impact of gene selection methods on the reproducibility of profiling data in terms of differentially expressed genes using distinct reference RNA samples. The real-world toxicogenomic data set reported here showed high concordance in intersite and cross-platform comparisons. Further, gene lists generated by fold-change ranking were more reproducible than those obtained by t-test P value or Significance Analysis of Microarrays. Finally, gene lists generated by fold-change ranking with a nonstringent P-value cutoff showed increased consistency in Gene Ontology terms and pathways, and hence the biological impact of chemical exposure could be reliably deduced from all platforms analyzed.