Summarize Exposure Variables — run_summarize

Computes summary statistics for numeric exposure variables and optionally stores the results in the MultiAssayExperiment metadata.

Usage

run_summarize_exposures(expomicset, exposure_cols = NULL, action = "add")

Arguments

expomicset: A MultiAssayExperiment object containing exposure data in the sample metadata.
exposure_cols: A character vector of exposure variable names to summarize. If NULL, all numeric exposure variables are included.
action: A string specifying the action to take. Use "add" to attach the summary table to metadata(expomicset) or "get" to return the summary table directly. Default is "add".

Value

A modified MultiAssayExperiment object (if action = "add"), or a data frame of summary statistics (if action = "get").

Details

This function:

Extracts sample-level exposure data using pivot_sample().
Filters to user-specified exposures (exposure_cols) if provided.
Computes descriptive statistics for each numeric variable:
- Number of values (n_values)
- Number of NAs (n_na)
- Minimum, maximum, and range
- Sum, median, mean
- Standard error of the mean
- 95% confidence interval of the mean
- Variance, standard deviation
- Coefficient of variation (sd / mean)
Merges the result with variable metadata stored in metadata(expomicset)$codebook.

Examples

# Create example data
mae <- make_example_data(
    n_samples = 20,
    return_mae = TRUE
)
#> Ensuring all omics datasets are matrices with column names.
#> Creating SummarizedExperiment objects.
#> Creating MultiAssayExperiment object.
#> MultiAssayExperiment created successfully.

# Summarize exposure data
exp_sum <- mae |>
    run_summarize_exposures(
        exposure_cols = c("age", "bmi", "exposure_pm25"),
        action = "get"
    )