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DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data

机译：DCGL：R包，用于识别差异共表达的基因和基因表达微阵列数据中的链接

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摘要

Gene coexpression analysis was developed to explore gene interconnection at the expression level from a systems perspective, and differential coexpression analysis (DCEA), which examines the change in gene expression correlation between two conditions, was accordingly designed as a complementary technique to traditional differential expression analysis (DEA). Since there is a shortage of DCEA tools, we implemented in an R package 'DCGL' five DCEA methods for identification of differentially coexpressed genes and differentially coexpressed links, including three currently popular methods and two novel algorithms described in a companion paper. DCGL can serve as an easy-to-use tool to facilitate differential coexpression analyses.
机译：开展基因共表达分析以从系统角度探讨表达水平上的基因互连，并相应地设计了检测两种条件之间基因表达相关性变化的差异共表达分析（DCEA），作为传统差异表达分析的补充技术。 （数据包络分析）。由于缺少DCEA工具，我们在R包“ DCGL”中实施了五种DCEA方法，用于鉴定差异共表达的基因和差异共表达的链接，其中包括三种当前流行的方法和在伴侣论文中描述的两种新颖算法。 DCGL可以用作易于使用的工具，以促进差异共表达分析。

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