Children's Medical Center Research Institute at UT Southwestern Medical Center, 6000 Harry Hines Blvd, Dallas, TX, 75235, USA.
Quantitative Biomedical Research Center at UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA.
Nat Commun. 2017 Dec 19;8(1):2187. doi: 10.1038/s41467-017-02181-0.
Co-expression analysis is widely used to predict gene function and to identify functionally related gene sets. However, co-expression analysis using human cancer transcriptomic data is confounded by somatic copy number alterations (SCNA), which produce co-expression signatures based on physical proximity rather than biological function. To better understand gene-gene co-expression based on biological regulation but not SCNA, we describe a method termed "Genomic Regression Analysis of Coordinated Expression" (GRACE) to adjust for the effect of SCNA in co-expression analysis. The results from analyses of TCGA, CCLE, and NCI60 data sets show that GRACE can improve our understanding of how a transcriptional network is re-wired in cancer. A user-friendly web database populated with data sets from The Cancer Genome Atlas (TCGA) is provided to allow customized query.
共表达分析被广泛用于预测基因功能和识别功能相关的基因集。然而，使用人类癌症转录组数据进行共表达分析受到体细胞拷贝数改变（SCNAs）的干扰，这些改变基于物理邻近性而不是生物功能产生共表达特征。为了更好地理解基于生物调控而非 SCNAs 的基因-基因共表达，我们描述了一种称为“共表达的基因组回归分析”（GRACE）的方法，以调整共表达分析中 SCNAs 的影响。对 TCGA、CCLE 和 NCI60 数据集的分析结果表明，GRACE 可以帮助我们更好地理解转录网络在癌症中是如何重新布线的。提供了一个用户友好的网络数据库，其中包含来自癌症基因组图谱（TCGA）的数据，以允许进行自定义查询。
