Cluster analysis and display of genome-wide expression patterns
Cluster analysis and display of genome-wide expression patterns
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DOI：
10.1073/pnas.95.25.14863
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发表时间：
1998-12-08
影响因子：
11.1
通讯作者：
Botstein, D
中科院分区：
文献类型：
--
作者：
Eisen, MB;Spellman, PT;Botstein, D
一个系统的聚类分析全基因组表达数据的DNA微阵列杂交，使用标准的统计算法来安排基因，根据基因表达模式的相似性。输出以图形方式显示，以生物学家直观的形式同时传达聚类和底层表达数据。我们在芽殖酵母酿酒酵母中发现，聚类基因表达数据可以有效地将已知功能相似的基因分组在一起，我们在人类数据中也发现了类似的趋势。因此，在全基因组表达实验中看到的模式可以被解释为细胞过程状态的指示。此外，已知功能的基因与表征不佳的或新的基因的共表达可以提供一种简单的方法，以获得目前无法获得信息的许多基因的功能。
A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.