Run Exposure-Omics Association — run_exposure_omics

Test associations between each exposure and each omics feature using limma's linear modeling framework.

Usage

run_exposure_omics_association(
  exposomicset,
  exposures = NULL,
  exp_name = NULL,
  covariates = NULL,
  scaling_method = "none",
  correction_method = "fdr",
  top_pct = NULL,
  filter_by = c("variance", "mean"),
  action = "add"
)

Arguments

exposomicset: A MultiAssayExperiment object containing exposome and omics data.
exposures: Character vector of exposure variable names to test. If NULL, uses all variables from the codebook.
exp_name: Name(s) of the omics assay(s) to test against. If NULL, uses all assays.
covariates: Optional character vector of covariate names to include in the model.
scaling_method: Character. Scaling method to apply before modeling. Options include "none" (default).
correction_method: Method for p-value adjustment. Default is "fdr".
top_pct: Top X% of features to retain using either mean or variance which is specified by filter_by. If NULL, no features will be filtered.
filter_by: Determination of how to filter omics features either by mean or variance.
action: If "add" (default), saves results to metadata, if "get", returns results as a data frame.

Value

If action = "add", returns updated MultiAssayExperiment. Otherwise, returns a tibble with association results.

Details

This function uses limma to test associations between multiple exposures and omics features. For each exposure, a linear model is fit with the exposure as the predictor and each omics feature as the outcome, adjusting for covariates.

omics_feature ~ exposure + covariate1 + covariate2 + ...

Examples

# create example data
mae <- make_example_data(
    n_samples = 10,
    return_mae = TRUE
)
#> Ensuring all omics datasets are matrices with column names.
#> Creating SummarizedExperiment objects.
#> Creating MultiAssayExperiment object.
#> MultiAssayExperiment created successfully.

# run exposure-omics association
mae <- mae |>
    run_exposure_omics_association(
        exposures = c("exposure_pm25", "exposure_no2"),
        covariates = c("age", "sex")
    )
#> Testing 2 exposures across 2 assays
#> Processing assay: mRNA
#> Processing assay: proteomics