CMCS: classifying and analyzing clustered somatic mutations to elucidate the potential contributions in tumorigenesis.

Abstract

Clustered somatic mutations, which are common in cancer genomes and play critical roles in both pathological and physiological processes, are frequently accumulated in specific genomic regions. To enable efficient identification of these clustered mutations and gain insights into the potential functions of the associated genes in cancer, we developed the Cluster Mutation Classification System (CMCS; https://www.tmliang.cn/cluster/), a user-friendly web-based platform. CMCS aimed to screen genes harboring multiple clustered mutations based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm and simultaneously estimate the potential molecular features and biological roles in tumorigenesis. The platform allows users to screen and analyze clustered somatic mutations to characterize mutation types, related genes, mutation ranges, and annotations. Furthermore, it facilitates downstream analyses of these genes, uncovering molecular alterations and potential clinical implications across various molecular levels. CMCS provides insights into the molecular characteristics of genes harboring clustered mutations by leveraging a multiomics approach, enriching our understanding of their relationships to cancer development and progression.