olink_wilcox {OlinkAnalyze}

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, ...)

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.

...

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

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)

Examples

library(dplyr)

npx_df <- npx_data1 %>% filter(!grepl('control',SampleID, ignore.case = TRUE))

wilcox_results <- olink_wilcox(df = npx_df,
                               variable = 'Treatment',
                               alternative = 'two.sided')

#Paired Mann-Whitney U Test
npx_df %>%
   filter(Time %in% c("Baseline","Week.6")) %>%
   olink_wilcox(variable = "Time", pair_id = "Subject")