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Current Bioinformatics

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ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

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Research Article

Prediction of Cancer Driver Genes through Integrated Analysis of Differentially Expressed Genes at the Individual Level

Author(s): Bo Gao, Yue Zhao and Guojun Li*

Volume 18, Issue 10, 2023

Published on: 27 September, 2023

Page: [792 - 804] Pages: 13

DOI: 10.2174/1574893618666230524142013

Price: $65

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Abstract

Introduction: It is expected that certain driver mutations may alter the gene expression of their associated or interacting partners, including cognate proteins.

Methods: We introduced DEGdriver, a novel method that can discriminate between mutations in drivers and passengers by utilizing gene differential expression at the individual level.

Results: After being tested on eleven TCGA cancer datasets, DEGdriver substantially outperformed cutting-edge approaches in distinguishing driver genes from passengers and exhibited robustness to varying parameters and protein-protein interaction networks.

Conclusion: Through enrichment analysis, we prove that DEGdriver can identify functional modules or pathways in addition to novel driver genes.

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