OlinkAnalyze (version 5.1.0)

olink_wilcox: Function which performs a Mann-Whitney U Test per protein

Description

Performs a Welch 2-sample Mann-Whitney U Test at confidence level 0.95 for every protein (by OlinkID) for a given grouping variable using stats::wilcox.test and corrects for multiple testing by the Benjamini-Hochberg method (“fdr”) using stats::p.adjust. Adjusted p-values are logically evaluated towards adjusted p-value<0.05. The resulting Mann-Whitney U Test table is arranged by ascending p-values.

Usage

olink_wilcox(df, variable, pair_id, check_log = NULL, ...)

Value

A data frame containing the Mann-Whitney U Test results for every protein. Columns include:

• Assay: "character" Protein symbol

• OlinkID: "character" Olink specific ID

• UniProt: "character" UniProt ID

• Panel: "character" Name of Olink Panel

• estimate: "numeric" median of NPX differences between groups

• statistic: "named numeric" the value of the test statistic with a name describing it

• p.value: "numeric" p-value for the test

• conf.low: "numeric" confidence interval for the median of differences (lower end)

• conf.high: "numeric" confidence interval for the median of differences (upper end)

• method: "character" which wilcoxon method was used

• alternative: "character" describes the alternative hypothesis

• Adjusted_pval: "numeric" adjusted p-value for the test (Benjamini&Hochberg)

• Threshold: "character" if adjusted p-value is significant or not (< 0.05)

Arguments

df

NPX or Quantified_value data frame in long format with at least protein name (Assay), OlinkID, UniProt and a factor with 2 levels.

variable

Character value indicating which column should be used as the grouping variable. Needs to have exactly 2 levels.

pair_id

Character value indicating which column indicates the paired sample identifier.

check_log

Optional named list returned by check_npx(). If NULL, an attached check_log is used when present; otherwise check_npx() will be run internally using df.

...

Options to be passed to wilcox.test. See ?wilcox_test for more information.

Examples

# \donttest{
if (rlang::is_installed(pkg = c("broom"))) {
  npx_df <- npx_data1 |>
    dplyr::filter(
    !grepl(
      pattern = "control",
      x = .data[["SampleID"]],
      ignore.case = TRUE
    )
  )

  # Mann-Whitney U Test
  wilcox_results <- OlinkAnalyze::olink_wilcox(
    df = npx_df,
    variable = "Treatment",
    alternative = "two.sided"
  )

  # Paired Mann-Whitney U Test
  wilcox_paired_results <- npx_df |>
    dplyr::filter(
      .data[["Time"]] %in% c("Baseline", "Week.6")
    ) |>
    OlinkAnalyze::olink_wilcox(
      variable = "Time",
      pair_id = "Subject"
    )
}
# }