Bootstrap Evaluation of Association Matrices (BEAM) for Integrating Multiple Omics Profiles with Multiple Outcomes.

ABSTRACT:

Motivation

Large datasets containing multiple clinical and omics measurements for each subject motivate the development of new statistical methods to integrate these data to advance scientific discovery.

Model

We propose bootstrap evaluation of association matrices (BEAM), which integrates multiple omics profiles with multiple clinical endpoints. BEAM associates a set omic features with clinical endpoints via regression models and then uses bootstrap resampling to determine statistical significance of the set. Unlike existing methods, BEAM uniquely accommodates an arbitrary number of omic profiles and endpoints.

Results

In simulations, BEAM performed similarly to the theoretically best simple test and outperformed other integrated analysis methods. In an example pedia

SUBMITTER: Seffernick AE 

PROVIDER: S-EPMC11312528 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature