DriverDBv4: A database for human cancer driver gene research



The Cancer Summary section provides a Summary network that integrates cancer dysfunction and dysregulation events at a multi-omics level, and a Driver summary table that summarizes driver events identified in each omics.


Summary network

Node:


Driver summary table


The Cancer Mutation function visualizes the mutation drivers identified by bioinformatics tools in a particular cancer type. These mutation drivers are prioritized, and the distribution of mutations is presented.


mutation driver defined by tools

The plot indicates defined mutation driver numbers by different number of computational tools according to the mutation summary table.

Mutation Summary Table


Visualization of Top 30 genes

This plot illustrates the relations between the top 30 mutation driver genes and cancer patients; the samples of cancer patients are on the x-axis and the top 30 genes are on the y-axis.

This plot shows the top 30 genes on the y-axis and the number of tools by which they are defined on x-axis.


The Cancer CNV provides visualizations to illustrate the genes with a high copy number variation (CNV) gain or loss in a specific cancer type. The distribution of CNV Drivers in pan-cancer and chromosomes are presented.


Visualization of:


Visualization of Top 30 genes

This bar chart provides an overview of the CNV percentages for each of the top 30 genes in a specific cancer type.


This plot illustrates the relations between the top 30 genes and their CNV in cancer patients for a specific cancer type; the samples of cancer patients are on the x-axis and the top 30 genes are on the y-axis.


Locus enrichment

The Locus Enrichment graph marks the loci on each chromosome using a red dot. Hover over the dots to see detailed information such as the chromosome number, position, value and gene symbol.



CNV table


The Cancer Methylation function provides visualizations to illustrate the genes with a high methylation in a specific cancer type. The distribution of Methylation Drivers in pan-cancer and chromosomes are displayed.


Visualization of:


Visualization of Top 30 genes

This bar chart provides an overview of the methylation percentages for each of the top 30 genes in a certain cancer type.


This plot illustrates the relations between the top 30 genes and their methylation type in cancer patients for a certain cancer type; the samples of cancer patients are on the x-axis and the top 30 genes are on the y-axis.


Locus enrichment

The Locus Enrichment graph marks the loci on each chromosome using a red dot. Hover over the dots to see detailed information such as the chromosome number, position, value and gene symbol.



Methylation table


The Cancer Survival function visualizes the survival probability under the synergistic effect of gene pairs in a specific cancer type.


Survival network

The Cancer Survival network illustrates the synergistic effect between significant survival-relevant genes. The synergistic effect is defined by the hazard ratio (HR) of two genes, and has 2 levels – 1.5 folds and 2 folds; each with a positive (>1) and negative (<1) direction of HR.


Survival of synergistic effect

This section includes all gene pairs with HR fold change greater than 1.5 in both directions. For each gene pair, the patients are stratified to groups based on their levels of expression for the genes. The groups of patients are then compared on their survival probability over months, as shown in the plots.


The Cancer miRNA function provides visualizations to illustrate the relations between differentially expressed (DE) genes and miRNAs in a specific cancer type. You can explore the connections between genes and miRNAs in the following sections.


Cancer miRNA network

The Cancer miRNA network illustrates the relations between differentially expressed (DE) genes and miRNAs as identified by bioinformatics tools. Validated relations are represented by solid lines; whereas predicted relations are represented by dotted lines. Predicted relations can be further filtered by a minimum of 6, 8, or 10 tools.


Visualization by

Visualization of differential expressed gene and miRNA

This heat map illustrates the relations between differentially expressed (DE) genes/miRNAs and cancer patients for a certain cancer type; the samples of cancer patients are on the x-axis and the DE genes/miRNAs are on the y-axis.

Gene-miRNA table


The Cancer Multi-omics function provides visualizations to illustrate genes of a specific cancer type identified by multi-omics integration tools. It prioritizes multi-omics drivers and presents their distributions in miRNA, mRNA, CNV, mutations, and methylation data.


Visualization of:


Multi-omics driver related biological functions

This diagram illustrates the associations between multi-omics, genes, and Gene Ontology (GO) terms of a specific cancer type. You can switch the radio button to view the result of different gene datasets. Nodes in the graph with more connections indicate a higher level of influence. Detailed information and results are listed in the table below the diagram.


Visualiztion of multiomics drivers distribution

The following visualizations display the adopted tools and the identified driver genes of five omics, mRNA, miRNA, CNV, mutation, and methylation. The left side shows a heatmap depicting the correlation between genes and omics, and the right bar chart displays the top genes chosen by the most tools.



Drivers defined by multi-omics tools

The following visualizations display the number of genes selected by multi-omics tools. The left heatmap illustrates the association between tools and omics and the right bar chart shows the distribution of the selected gene number by different tool counts.






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