DEDUCE: statistical inference on disease-associated genes uncovers tissue-disease associations.

ABSTRACT: Accurate identification of affected tissues of human diseases is important for the derivation of disease etiology and the development of new treatment strategies. In this study, we develop a logistic regression-based method named DEDUCE (disease tissue detection using logistic regression) that combines genomics big data and machine learning to address this important problem. The central hypothesis is that most disease-associated genes are expressed specifically in affected tissues. DEDUCE takes advantage of newly emerged data on disease-related genes as well as tissue-specific gene expression data. The unique feature of DEDUCE is that it takes into account the strength of gene-disease associations. When we applied DEDUCE to a total of 3261, 324 gene-disease associations collected from DisG

SUBMITTER: Wang B 

PROVIDER: S-EPMC12754781 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature