OSCA

OSCA performs association analysis of complex traits using multi-omics data, with particular emphasis on DNA methylation (DNAm).

Key Features:

• MOMENT (Modeling Omics with Multiple Effectors for Trait association): A mixed-linear-model-based approach implemented in OSCA for testing probe–trait associations.
• DNAm probe–trait testing: Tests associations between a DNAm probe and a trait while explicitly modeling other distal probes.
• Multiple random-effect components: Uses multiple random-effect components to account for the effects of distal probes and control for unobserved confounders.
• Simulation validation: Demonstrated in simulations to have a lower false positive rate and enhanced robustness compared to existing methods.
• Multi-omics support: Applies to omic profiles beyond DNAm within large cohort studies.
• Suite of implementations: Includes additional analytical implementations for comprehensive omic-data-based analyses.

Scientific Applications:

• Complex trait association studies: Association analysis of complex traits using multi-omics data, with a focus on DNAm.
• DNAm-trait discovery: Identification of DNAm probes associated with traits while accounting for distal-probe confounding.
• Large-cohort omic analyses: Analysis of omic profile–trait relationships in large cohort datasets.

Methodology:

MOMENT implements a mixed-linear-model-based association test that models a focal DNAm probe and incorporates multiple random-effect components for distal probes; performance was evaluated using simulations reporting lower false positive rate and increased robustness.