olink_bridgeselector: Bridge selection function

View source: R/Olink_bridgeselector.R

olink_bridgeselectorR Documentation

Description

The bridge selection function will select a number of bridge samples based on the input data. It selects samples with good detection, which passes QC and cover a good range of the data.

Usage

olink_bridgeselector(df, sampleMissingFreq, n)

Arguments

df

Tibble/data frame in long format such as produced by the Olink Analyze read_NPX function.

sampleMissingFreq

The threshold for sample wise missingness.

n

Number of bridge samples to be selected.

Details

When running the selector, the sampleMissingFreq value represents a maximum percentage of data below LOD allowed per sample. When running plasma on smaller panels, such as Target 96, sampleMissingFreq = 0.10 can be a good starting point. Larger panels such as Explore HT have many proteins that are only expressed in certain diseases or matrices and therefore more data below LOD is expected. In this case sampleMissingFreq = 0.5 can be a good starting point.

For more information, please consult the Introduction to Bridging tutorial.

The function accepts NPX Excel files with data < LOD replaced.

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

bridge_samples <- olink_bridgeselector(npx_data1, sampleMissingFreq = 0.1, n = 20)

OlinkAnalyze documentation built on Nov. 5, 2025, 5:25 p.m.