gcMECM: graph clustering of mutual exclusivity of cancer mutations

BMC Bioinformatics

Ying Hu¹  Qingrong Chen¹  Chunhua Yan¹  Daoud Meerzaman¹ 

[1] Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, USA;

关键词: Cancer driver genes;    Mutually exclusive mutations;    Network analysis;    R package;   

DOI  :  10.1186/s12859-021-04505-w

来源: Springer

【 摘 要 】

BackgroundNext-generation sequencing platforms allow us to sequence millions of small fragments of DNA simultaneously, revolutionizing cancer research. Sequence analysis has revealed that cancer driver genes operate across multiple intricate pathways and networks with mutations often occurring in a mutually exclusive pattern. Currently, low-frequency mutations are understudied as cancer-relevant genes, especially in the context of networks.ResultsHere we describe a tool, gcMECM, that enables us to visualize the functionality of mutually exclusive genes in the subnetworks derived from mutation associations, gene–gene interactions, and graph clustering. These subnetworks have revealed crucial biological components in the canonical pathway, especially those mutated at low frequency. Examining the subnetwork, and not just the impact of a single gene, significantly increases the statistical power of clinical analysis and enables us to build models to better predict how and why cancer develops.ConclusionsgcMECM uses a computationally efficient and scalable algorithm to identify subnetworks in a canonical pathway with mutually exclusive mutation patterns and distinct biological functions.

【 授权许可】

CC BY