Hypervariable genes-experimental error or hidden dynamics
Hypervariable genes-experimental error or hidden dynamics
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DOI：
10.1093/nar/gnh146
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发表时间：
2004-01-01
影响因子：
14.9
通讯作者：
Centola, M
中科院分区：
文献类型：
--
作者：
Dozmorov, I;Knowlton, N;Centola, M
在同一组样本中，并不是所有高变异性的基因都源于微阵列实验中的实验错误。这些表达的变化可以归因于许多因素，包括自然的生物振荡或代谢过程。这些基因的行为可以梳理出关于所研究的生物体或实验系统中自然发生的动态过程的重要线索。我们开发了一种统计程序来选择具有高变异性的基因，即高变量(HV)基因。在排除低表达基因和稳定的对数转化后，大多数基因具有类似的残留变异性。基于F检验，HV基因被选为具有统计学意义上的差异，而大多数变异性稳定的基因是由“参照组”测量的。一种新的F-检验聚类技术，又被称为‘F-均值聚类’，将具有相似变异模式的HV基因分组，推测是因为它们参与了一个共同的动态生物过程。F-Means聚类法首次建立了共表达的HV基因组，并用来自幼年类风湿性关节炎患者和健康对照的微阵列数据进行了说明。
In a homogeneous group of samples, not all genes of high variability stem from experimental errors in microarray experiments. These expression variations can be attributed to many factors including natural biological oscillations or metabolic processes. The behavior of these genes can tease out important clues about naturally occurring dynamic processes in the organism or experimental system under study. We developed a statistical procedure for the selection of genes with high variability denoted hypervariable (HV) genes. After the exclusion of low expressed genes and a stabilizing log-transformation, the majority of genes have comparable residual variability. Based on an F-test, HV genes are selected as having a statistically significant difference from the majority of variability stabilized genes measured by the 'reference group'. A novel F-test clustering technique, further noted as 'F-means clustering', groups HV genes with similar variability patterns, presumably from their participation in a common dynamic biological process. F-means clustering establishes, for the first time, groups of co-expressed HV genes and is illustrated with microarray data from patients with juvenile rheumatoid arthritis and healthy controls.