CONVEX APPROACHES TO ISOLATE THE SHARED AND DISTINCT GENETIC STRUCTURES OF SUBPHENOTYPES IN HETEROGENEOUS COMPLEX TRAITS.

ABSTRACT: Groups of complex diseases, such as coronary heart diseases, neuropsychiatric disorders, and cancers, often display overlapping clinical symptoms and pharmacological treatments. The shared associations of genetic variants across diseases has the potential to explain their underlying biological processes, but this remains poorly understood. To address this, we model the matrix of summary statistics of trait-associated genetic variants as the sum of a low-rank component - representing shared biological processes - and a sparse component, representing unique processes and arbitrarily corrupted or contaminated components. We introduce Clorinn, an open-source Python software that uses convex optimization algorithms to recover these components by minimizing a weighted combination of the nuclear

SUBMITTER: Banerjee S 

PROVIDER: S-EPMC12047927 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature