clean_npx: Clean proteomics data quantified with Olink's PEA technology
In OlinkAnalyze: Facilitate Analysis of Proteomic Data from Olink

clean_npx

R Documentation

Clean proteomics data quantified with Olink's PEA technology

Description

This function applies a series of cleaning steps to a data set exported by Olink Software and imported in R by read_npx(). Some of the steps of this function rely on results from check_npx().

This function removes samples and assays that are not suitable for downstream statistical analysis. Some of the data records that are removed include duplicate sample identifiers, external controls samples, internal control assays, and samples or assays with quality control flags.

Usage

clean_npx(
  df,
  check_log = NULL,
  remove_assay_na = TRUE,
  remove_invalid_oid = TRUE,
  remove_dup_sample_id = TRUE,
  remove_control_assay = TRUE,
  remove_control_sample = TRUE,
  remove_qc_warning = TRUE,
  remove_assay_warning = TRUE,
  control_sample_ids = NULL,
  convert_df_cols = TRUE,
  convert_nonunique_uniprot = TRUE,
  out_df = "tibble",
  verbose = FALSE
)

Arguments

`df`	A "tibble" or "ArrowObject" from `read_npx`.
`check_log`	A named list returned by `check_npx()`. If `NULL`, `check_npx()` will be run internally using `df`.
`remove_assay_na`	Logical. If `FALSE`, skips filtering assays with all quantified values `NA`. Defaults to `TRUE`.
`remove_invalid_oid`	Logical. If `FALSE`, skips filtering assays with invalid identifiers. Defaults to `TRUE`.
`remove_dup_sample_id`	Logical. If `FALSE`, skips filtering samples with duplicate sample identifiers. Defaults to `TRUE`.
`remove_control_assay`	If `FALSE`, all internal control assays are retained. If `TRUE`, all internal control assays are removed. Alternatively, a character vector with one or more of "assay", "inc", "det", "ext", and "amp" indicating the assay types to remove.
`remove_control_sample`	If `FALSE`, all control samples are retained. If `TRUE`, all control samples are removed. Alternatively, a character vector with one or more of "sample", "sc", "pc", "nc", "calibrator", and "other" indicating the sample types to remove.
`remove_qc_warning`	Logical. If `FALSE`, retains samples flagged as `FAIL` in QC warning. Defaults to `TRUE`.
`remove_assay_warning`	Logical. If `FALSE`, retains assays flagged as `WARN` in assay warning. Defaults to `TRUE`.
`control_sample_ids`	character vector of sample identifiers of control samples. Default `NULL`, to mark no samples to be removed.
`convert_df_cols`	Logical. If `FALSE`, retains columns of `df` as are. Defaults to `TRUE`, were columns required for downstream analysis are converted to the expected format.
`convert_nonunique_uniprot`	Logical. If `FALSE`, retains non-unique OlinkID - UniProt mapping. Defaults to `TRUE`.
`out_df`	The class of the output dataset. One of "tibble" or "arrow". Defaults to "tibble".
`verbose`	Logical. If `FALSE` (default), silences step-wise messages.

Details

The pipeline performs the following steps:

Remove assays with invalid identifiers: assays flagged as having invalid identifiers from check_npx(). Occurs when the original data set provided by Olink Software has been modified.
Remove assays with NA quantification values: assays lacking quantification data are reported with NA as quantification. These assays are identified in check_npx().
Remove samples with duplicate identifiers: samples with identical identifiers detected by check_npx(). Instances of duplicate sample identifiers cause errors in the downstream analysis of data with, and it is highly discouraged.
Remove external control samples:
- Uses column marking sample type (e.g. SampleType) to exclude external control samples.
- Uses column marking sample identifier (e.g. SampleID) to remove external control samples, or samples that ones wants to exclude from the downstream analysis.
Remove samples failing quality control: samples with QC status FAIL.
Remove internal control assays: Uses column marking assay type (e.g. AssayType) to exclude internal control assays.
Remove assays with quality controls warnings: assays with QC status WARN.
Correct column data type: ensure that certain columns have the expected data type (class). These columns are identified in check_npx().
Resolve multiple UniProt mappings per assay: ensure that each assay identifier (e.g., OlinkID) maps uniquely to a single UniProt ID.

Important:

When data set lacks a column marking sample type (e.g. SampleType), one should remove external control samples based on their sample identifiers. This function does not auto-detect external control samples based on their sample identifiers. Please ensure external control samples have been removed prior to downstream statistical analysis.
When data set lacks a column marking assay type (e.g. AssayType), one should remove internal control assays manually. This function does not auto-detect internal control assays. Please ensure internal control assays have been removed prior to downstream statistical analysis.

Value

Dataset, "tibble" or "ArrowObject", with Olink data in long format.

Author(s)

Kang Dong Klev Diamanti

Examples

## Not run: 
# run check_npx
check_log <- check_npx(
  df = npx_data1
)

# run clean_npx
clean_npx(
  df = npx_data1,
  check_log = check_log
)

# run clean_npx with messages for all steps
clean_npx(
  df = npx_data1,
  check_log = check_log,
  verbose = TRUE
)

## End(Not run)

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