Dataset Information

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 pediatric leukemia application, BEAM identified several genes with biological relevance established by a CRISPR assay that had been missed by univariate screens and other integrated analysis methods. Thus, BEAM is a powerful, flexible, and robust tool to identify genes for further laboratory and/or clinical research evaluation.

Availability

Source code, documentation, and a vignette for BEAM are available on GitHub at: https://github.com/annaSeffernick/BEAMR. The R package is available from CRAN at: https://cran.r-project.org/package=BEAMR.

Contact

Stanley.Pounds@stjude.org.

Supplementary information

Supplementary data are available at the journal's website.

SUBMITTER: Seffernick AE

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

REPOSITORIES: biostudies-literature

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Publications

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

Seffernick Anna Eames AE Cao Xueyuan X Cheng Cheng C Yang Wenjian W Autry Robert J RJ Yang Jun J JJ Pui Ching-Hon CH Teachey David T DT Lamba Jatinder K JK Mullighan Charles G CG Pounds Stanley B SB

bioRxiv : the preprint server for biology 20240803

<h4>Motivation</h4>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.<h4>Model</h4>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 statis ...[more]

PMID: 39131398

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Dataset Information

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

Motivation

Model

Results

Availability

Contact

Supplementary information

Publications

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

Similar Datasets

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