HCCDB: A Database of Hepatocellular Carcinoma Expression Atlas.
10.1016/j.gpb.2018.07.003
- Author:
Qiuyu LIAN
1
;
Shicheng WANG
1
;
Guchao ZHANG
1
;
Dongfang WANG
1
;
Guijuan LUO
2
;
Jing TANG
2
;
Lei CHEN
3
;
Jin GU
4
Author Information
1. MOE Key Laboratory of Bioinformatics, Beijing National Research Center for Information Science and Technology, Bioinformatics Division, Department of Automation, Tsinghua University, Beijing 100084, China.
2. International Co-operation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute, Second Military Medical University, Shanghai 200438, China.
3. International Co-operation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Institute, Second Military Medical University, Shanghai 200438, China. Electronic address: chenlei@smmu.edu.cn.
4. MOE Key Laboratory of Bioinformatics, Beijing National Research Center for Information Science and Technology, Bioinformatics Division, Department of Automation, Tsinghua University, Beijing 100084, China. Electronic address: jgu@tsinghua.edu.cn.
- Publication Type:Journal Article
- Keywords:
Database;
Hepatocellular carcinoma;
Integrative analysis;
Meta-analysis;
Transcriptome
- MeSH:
Carcinoma, Hepatocellular;
genetics;
Databases, Genetic;
Gene Expression Profiling;
Gene Expression Regulation, Neoplastic;
Humans;
Liver Neoplasms;
genetics
- From:
Genomics, Proteomics & Bioinformatics
2018;16(4):269-275
- CountryChina
- Language:English
-
Abstract:
Hepatocellular carcinoma (HCC) is highly heterogeneous in nature and has been one of the most common cancer types worldwide. To ensure repeatability of identified gene expression patterns and comprehensively annotate the transcriptomes of HCC, we carefully curated 15 public HCC expression datasets that cover around 4000 clinical samples and developed the database HCCDB to serve as a one-stop online resource for exploring HCC gene expression with user-friendly interfaces. The global differential gene expression landscape of HCC was established by analyzing the consistently differentially expressed genes across multiple datasets. Moreover, a 4D metric was proposed to fully characterize the expression pattern of each gene by integrating data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). To facilitate a comprehensive understanding of gene expression patterns in HCC, HCCDB also provides links to third-party databases on drug, proteomics, and literatures, and graphically displays the results from computational analyses, including differential expression analysis, tissue-specific and tumor-specific expression analysis, survival analysis, and co-expression analysis. HCCDB is freely accessible at http://lifeome.net/database/hccdb.
