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DriverDBv2: a database for human cancer driver gene research.

I-Fang Chung1, Chen-Yang Chen2, Shih-Chieh Su3

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DriverDBv2 enhances cancer research by integrating over 16,500 RNA-seq and exome-seq datasets. This updated database aids in identifying driver genes and mutations, offering new visualization tools for expression and mutation hotspots.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • DriverDB is a database for identifying cancer driver genes and mutations.
  • It previously incorporated ~6000 exome-seq datasets and bioinformatics algorithms.
  • The database offers 'Cancer' and 'Gene' views for relationship visualization.

Purpose of the Study:

  • To present the updated DriverDBv2 database with expanded datasets and enhanced functionalities.
  • To improve the identification and analysis of cancer driver genes and mutations.
  • To provide researchers with advanced tools for exploring genomic and clinical data.

Main Methods:

  • Incorporated >9500 cancer-related RNA-seq and >7000 exome-seq datasets from TCGA, ICGC, and publications.
  • Integrated seven additional computational algorithms for driver gene identification, totaling 15 algorithms.
  • Developed new 'Expression' and 'Hotspot' features in the 'Gene' section and a 'Gene Set' function.

Main Results:

  • DriverDBv2 now includes over 16,500 cancer-related datasets.
  • Fifteen computational algorithms are utilized for driver gene identification.
  • New features allow visualization of gene expression profiles, mutation hotspots, and gene set analyses.

Conclusions:

  • DriverDBv2 provides a significantly expanded and enhanced resource for cancer driver gene and mutation research.
  • The new features facilitate deeper investigation into the relationships between mutations, gene expression, and clinical data.
  • This updated database serves as a valuable tool for the cancer research community.