olink_bridge_selector: Bridge selection function

In OlinkAnalyze: Facilitate Analysis of Proteomic Data from Olink

Bridge selection function

Description

The bridge selection function will select a number of bridge samples based on the input data. It selects samples with good detection that pass QC and cover a good range of the data. If possible, Olink recommends 8-16 bridge samples. When running the selector, Olink recommends starting at sample_missing_freq = 0.10 which represents a maximum of 10\ per sample. If there are not enough samples output, increase to 20\ The function accepts NPX Excel files with data < LOD replaced.

Usage

olink_bridge_selector(df, sample_missing_freq, n, check_log = NULL)

olink_bridgeselector(df, ..., n, check_log = NULL)

Arguments

df	Tibble/data frame in long format such as produced by the Olink Analyze read_npx function.
sample_missing_freq	The threshold for sample wise missingness.
n	Number of bridge samples to be selected.
check_log	A named list returned by check_npx(). If NULL, check_npx() will be run internally using df.
...	Additional arguments. Currently only accepts sampleMissingFreq for backward compatibility. Please use sample_missing_freq instead of sampleMissingFreq in the future.

Details

olink_bridgeselector() is a synonym of olink_bridge_selector() .

Value

A "tibble" with sample IDs and mean NPX for a defined number of bridging samples. Columns include:

• SampleID: Sample ID

• PercAssaysBelowLOD: Percent of Assays that are below LOD for the sample

• MeanNPX: Mean NPX for the sample

Examples

  check_log <- OlinkAnalyze::check_npx(df = npx_data1)

  bridge_samples <- OlinkAnalyze::olink_bridge_selector(
    df = npx_data1,
    sample_missing_freq = 0.1,
    n = 20L,
    check_log = check_log
  )

OlinkAnalyze documentation built on June 24, 2026, 1:06 a.m.