School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, P.R. China.
Hunan Provincial Key Lab on Bioinformatics, Central South University, Changsha, Hunan 410083, P.R. China.
Nucleic Acids Res. 2022 Jan 7;50(D1):D710-D718. doi: 10.1093/nar/gkab1133.
Mapping gene interactions within tissues/cell types plays a crucial role in understanding the genetic basis of human physiology and disease. Tissue functional gene networks (FGNs) are essential models for mapping complex gene interactions. We present TissueNexus, a database of 49 human tissue/cell line FGNs constructed by integrating heterogeneous genomic data. We adopted an advanced machine learning approach for data integration because Bayesian classifiers, which is the main approach used for constructing existing tissue gene networks, cannot capture the interaction and nonlinearity of genomic features well. A total of 1,341 RNA-seq datasets containing 52,087 samples were integrated for all of these networks. Because the tissue label for RNA-seq data may be annotated with different names or be missing, we performed intensive hand-curation to improve quality. We further developed a user-friendly database for network search, visualization, and functional analysis. We illustrate the application of TissueNexus in prioritizing disease genes. The database is publicly available at https://www.diseaselinks.com/TissueNexus/.
在组织/细胞类型内绘制基因相互作用对于理解人类生理学和疾病的遗传基础至关重要。组织功能基因网络 (FGN) 是绘制复杂基因相互作用的重要模型。我们提出了 TissueNexus,这是一个数据库,其中包含通过整合异质基因组数据构建的 49 个人类组织/细胞系 FGN。我们采用了先进的机器学习方法进行数据集成,因为贝叶斯分类器(用于构建现有组织基因网络的主要方法)不能很好地捕获基因组特征的相互作用和非线性。总共整合了包含 52,087 个样本的 1,341 个 RNA-seq 数据集。由于 RNA-seq 数据的组织标签可能用不同的名称注释或缺失,因此我们进行了密集的手工编辑以提高质量。我们进一步开发了一个用户友好的数据库,用于网络搜索、可视化和功能分析。我们说明了 TissueNexus 在优先考虑疾病基因方面的应用。该数据库可在 https://www.diseaselinks.com/TissueNexus/ 上公开获取。