DriverDBv4:ã multi-omics integration database for cancer driv er g ene resear c h

Abstract

A dvãncements in high-throughput technology offer researchersãn e xtensiv e range of multi-omics data that provide deep insights into the complex landscape of cancer biology . However , traditional statistical modelsãnd databasesãre inadequate to interpret these high-dimensional data withinã multi-omics frame w ork. Toãddress this limitation, we introduce DriverDBv4,ãn updated iteration of the DriverDB cancer driver gene database ( http://driv erdb.bioinf omics.org/). T his updated v ersion offers se v eral significant enhancements: (i)ãn increase in the number of cohorts from 33 to 70, encompassingãpproximately 24 0 0 0 samples; (ii) inclusion of proteomics data,ãugmenting the existing types of omics dataãnd thus expanding theãnalytical scope; (iii) implementation of multiple multi-omicsãlgorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context dataãnd redesigned existing sections toãccommodate the increased volume of datasetsãnd (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identificationãnd subgroup e xpressionãnaly sis. Driv erDBv4 fãcilitates comprehensiv e interpretãtion of multi-omics datããcross diverse cancer types, thereby enriching the understanding of cancer heterogeneityãndãiding in the de v elopment of personalized clinicalãpproaches. The database is designed to fosterã more nuanced understanding of the multi-faceted nature of cancer.