Deciphering the Functional Roles of Individual Cancer Alleles Across Comprehensive Cancer Genomic Studies.

ABSTRACT: Cancer genome data has been growing in both size and complexity, primarily driven by advances in next-generation sequencing technologies, such as Pan-cancer data from TCGA, ICGC, and single-cell sequencing. Yet, discerning the functional role of individual genomic lesions remains a substantial challenge due to the complexity and scale of the data. Previously, we introduced REVEALER, which identifies groups of genomic alterations that significantly associate with target functional profiles or phenotypes, such as pathway activation, gene dependency, or drug response. In this paper, we present a new mathematical formulation of the algorithm. This version (REVEALER 2.0) is considerably more powerful than the original, allowing for rapid processing and analysis of much larger datasets and facil

SUBMITTER: Ma JY 

PROVIDER: S-EPMC10680728 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature