The effect of GeneChip gene definitions on the microarray study of cancers
The effect of GeneChip gene definitions on the microarray study of cancers
复制标题
GeneChip 基因定义对癌症微阵列研究的影响
DOI：
10.1002/bies.20433
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发表时间：
2006-07-01
期刊：
影响因子：
4
通讯作者：
Zhang, Xuegong
中科院分区：
文献类型：
--
作者：
Lu, Xuesong;Zhang, Xuegong
Affymetrix基因芯片是一种流行的全基因组表达谱微阵列平台，已广泛应用于功能基因组学，特别是癌症分类。由于基因组数据的更新，芯片设计时使用的许多基因组信息已经过时，并且据报道，当将探针映射到新的基因组信息时，芯片上的许多基因/转录本与其原始定义不同。Dai等人报道，更新的定义可能导致心脏组织表达谱数据集中选择的差异表达基因存在多达30-50%的差异。因此，理解这种差异的本质对于数据的利用非常重要。在这项工作中，我们以一个大型癌症数据集为例，比较了两种主要的定义，并研究了它们对分类、聚类、发现差异表达基因和基于基因集的分析的影响。结果表明，这两种定义在聚类和分类结果上是一致的，但被发现为差异表达或富集的基因和基因集可能存在很大差异。基于Affymetrix定义的发现可以涵盖大多数基于新定义的发现，但往往有更多的误报。
The Affymetrix GeneChip is a popular microarray platform for genome-wide expression profiling and has been widely used in functional genomics especially in the classification of cancers. Due to the updating of genome data, much of the genome information with which the chips were designed is out-of-date and it has been reported that many of the genes/transcripts on the chips differ from their original definition when mapping the probes to the new genome information. Dai et al. have reported that the updated definition can cause as much as 30-50% discrepancy in the genes selected as differentially expressed on a heart tissue expression profiling dataset. Understanding the nature of this difference is therefore very important for the utilization of the data. In this work, with a large cancer dataset as an example, we compared two major definitions and investigated their effects on classification, clustering, discovery of differentially expressed genes and gene-set-based analysis. Results show that the two definitions agree well on clustering and classification results but genes and gene sets discovered as differentially expressed or enriched can be very different. Discoveries based on the Affymetrix definition can cover most of those based on the new definition, but tend to have more false positives.