基因
微阵列分析技术
生物
生物途径
表型
遗传学
通路分析
基因表达
计算生物学
微阵列
基因表达谱
转录组
RNA序列
折叠变化
作者
Guini Hong,Wenjing Zhang,Hong‐Dong Li,Xiaopei Shen,Zheng Guo
标识
DOI:10.1098/rsif.2013.0950
摘要
Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.
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