View source: R/Olink_bridgeselector.R
| olink_bridgeselector | R Documentation |
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.
olink_bridgeselector(df, sampleMissingFreq, n)
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. |
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.
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
bridge_samples <- olink_bridgeselector(npx_data1, sampleMissingFreq = 0.1, n = 20)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.