TissueNexus: a database of human tissue functional gene networks built with a large compendium of curated RNA-seq data.
Cui-Xiang LinHong-Dong LiChao DengYuanfang GuanJian-Xin WangPublished in: Nucleic acids research (2021)
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/.
Keyphrases
- rna seq
- single cell
- copy number
- genome wide
- genome wide identification
- endothelial cells
- machine learning
- big data
- electronic health record
- induced pluripotent stem cells
- adverse drug
- stem cells
- gene expression
- artificial intelligence
- cell therapy
- pluripotent stem cells
- genome wide analysis
- deep learning
- bone marrow
- quality improvement
- mesenchymal stem cells
- high density