Coexpression analysis of human genes across many microarray data sets
Coexpression analysis of human genes across many microarray data sets
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DOI：
10.1101/gr.1910904
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发表时间：
2004-06-01
期刊：
影响因子：
7
通讯作者：
Pavlidis, P
中科院分区：
文献类型：
--
作者：
Lee, HK;Hsu, AK;Pavlidis, P
我们提出了一个大规模的分析mRNA共表达的基础上，60个大型人类数据集，共3924微阵列。我们在多个数据集中寻找可靠共表达的基因对（基于其表达谱的相关性），建立了由220，649个“共表达链接”连接的8805个基因的高置信度网络，这些基因在至少三个数据集中观察到。基因之间的正相关性比负相关性更常见。我们发现，确认在多个数据集的共表达与功能相关性，并显示如何聚类分析的网络可以揭示功能一致的基因组。我们的研究结果表明，大量积累的微阵列数据可以被利用，以增加有关基因功能的推断的可靠性。
We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in Multiple data sets, establishing a high-confidence network of 88O5 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function.