Statistical methods for ranking differentially expressed genes

被引:66
作者
Broberg, P [1 ]
机构
[1] AstraZeneca, Mol Sci, Res & Dev Lund, S-22187 Lund, Sweden
关键词
D O I
10.1186/gb-2003-4-6-r41
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
In the analysis of microarray data the identification of differential expression is paramount. Here I outline a method for finding an optimal test statistic with which to rank genes with respect to differential expression. Tests of the method show that it allows generation of top gene lists that give few false positives and few false negatives. Estimation of the false-negative as well as the false-positive rate lies at the heart of the method.
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收藏
页数:9
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