Welcome to OncoDB!
OncoDB2.0 is a comprehensive database developed for researchers and bioinformaticians to explore gene expression, DNA methylation, somatic mutations, proteomic profiles, and chromatin accessibility in the context of cancer. The database includes multi-omic data from approximately 10,000 patients, covering over 25,000 RefSeq genes across 33 cancer types, derived from the TCGA, GTEx, and CPTAC projects. The expression analysis module enables users to compare gene expression between tumor and normal tissues, identify highly differentially expressed genes, and examine gene-to-gene correlations. The methylation module allows for comparisons of DNA methylation (beta values) between cancer and normal samples, highlighting genes with significantly altered methylation patterns. The mutation analysis module provides oncogene mutation profiles derived from both DNA-seq and RNA-seq, along with information on associations between mutations, clinical parameters, and survival. The proteomic analysis module supports comparisons of protein expression between tumor and normal samples and provides a list of highly differentially expressed genes. Additionally, the chromatin accessibility analysis offers insights into oncogene regulation based on ATAC-seq peak data. The multi-omic analysis module enables users to explore correlations between gene expression and DNA methylation, as well as examine how expression and methylation levels vary with mutation status and mutation location. In the clinical analysis section, users can perform survival analysis based on gene expression and methylation using the Cox Proportional-Hazards Model and explore associations with various clinical parameters and subgroups. In addition to cancer-focused analyses, OncoDB2.0 also supports the exploration of gene expression, methylation, survival, and clinical correlations in the context of six major oncoviruses.

RNA Expression Proteomics DNA Methylation Somatic Mutation Chromatin Accessibility Multiomic Analysis Oncovirus Clinical Analysis
  • Cancer associated gene expression profile
  • Expression correlation of two different genes
  • Cancer associated proteomic expression profile
  • Differentially expressed proteomics in specified cancer
  • Cancer associated gene methylation profile
  • Differentially methylated genes in specified cancer
  • Mutation profile in tumor samples
  • Clinical analysis associated gene mutations
  • Cancer related chromosome accessibility
  • Differential chromosome accessibility in specified cancer
  • Gene expression/ methylation profiles in different mutation
  • Gene expression/ methylation correlation
  • Genomic profile related with viral infection
  • Clinical analysis related with viral infection
  • Survival analysis with gene expression/ methylation
  • Clinical profile with gene expression/ methylation
Expression Analysis Proteomic Analysis Methylation Analysis Mutation Analysis ATAC Analysis Multiomica Analysis Oncovirus Analysis Clinical Analysis









Reference:

  • Tang G, Liu X, Cho M, Li Y, Tran D, Wang X (2024) Pan-cancer discovery of somatic mutations from RNA sequencing data. Communications Biology, 7(1):619

  • Tang G, Cho M, Wang X (2022) OncoDB: an interactive online database for analysis of gene expression and viral infection in cancer. Nucleic Acids Research, 50(D1):D1334-D1339.