A powerful framework for differential co-expression analysis of general risk factors

Abstract excerpt

Differential co-expression analysis (DCA) aims to identify genes in a pathway whose shared expression depends on a risk factor. While DCA provides insights into the biological activity of diseases, existing methods are limited to categorical risk factors and/or suffer from bias due to batch and variance-specific effects. We propose a new framework, Kernel-based Differential Co-expression Analysis (KDCA), that harn...

Topics

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• Bioinformatics and Genomic Networks
• Computational Biology
• Disease
• Gene Expression Profiling
• Gene Expression Regulation
• Gene Regulatory Networks
• Genes
• Phenotype

Identifiers and source

Literature Corpus work

ad762861-b9aa-5e0e-8715-3244995edcd7

DOI

10.1101/2024.11.29.626006