Using biplots to interpret gene expression patterns in plants
Using biplots to interpret gene expression patterns in plants
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DOI：
10.1093/bioinformatics/18.1.202
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发表时间：
2002-01-01
期刊：
影响因子：
5.8
通讯作者：
Manners, J
中科院分区：
文献类型：
--
作者：
Chapman, S;Schenk, P;Manners, J
摘要：生态学、进化论、遗传学和育种领域的植物生物学家经常使用多元方法。本文说明了主成分分析(PCA)和Gabriel的双向图在植物病理学实验的微阵列表达数据中的应用。可用性：公开分发的统计语言R的示例程序可以从网站(www.tpp.uq.edu.au)获得，也可以通过联系的电子邮件获得。联系：scott.Chapman@csiro.au。
Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments.Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact.Contact: scott.chapman@csiro.au.