Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer's disease.

ABSTRACT: A large number of genetic variations have been identified to be associated with Alzheimer's disease (AD) and related quantitative traits. However, majority of existing studies focused on single types of omics data, lacking the power of generating a community including multi-omic markers and their functional connections. Because of this, the immense value of multi-omics data on AD has attracted much attention. Leveraging genomic, transcriptomic and proteomic data, and their backbone network through functional relations, we proposed a modularity-constrained logistic regression model to mine the association between disease status and a group of functionally connected multi-omic features, i.e. single-nucleotide polymorphisms (SNPs), genes and proteins. This new model was applied to the real da

SUBMITTER: Xie L 

PROVIDER: S-EPMC8574309 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature