Filter Sample Outliers — filter_sample_outliers • tidyexposomics

Removes sample outliers from a MultiAssayExperiment object based on PCA analysis.

Usage

filter_sample_outliers(expomicset, outliers = NULL)

Arguments

expomicset: A MultiAssayExperiment object containing omics and exposure data.
outliers: An optional character vector specifying sample names to be removed. If NULL, the function uses outliers identified in metadata(expomicset)$pca$outliers. Default is NULL.

Value

A MultiAssayExperiment object with the specified outliers removed.

Details

The function checks for the presence of PCA results in metadata(expomicset). If outliers is not provided, it retrieves precomputed outliers from metadata(expomicset)$pca$outliers. The identified samples are removed from the dataset.

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 PCA
mae <- mae |>
    run_pca()
#> Identifying common samples.
#> Subsetting exposure data.
#> Subsetting omics data.
#> Performing PCA on Feature Space.
#> Performing PCA on Sample Space.
#> No outliers detected.

# filter outliers if present
mae <- mae |>
    filter_sample_outliers()
#> Removing outliers: