OlinkAnalyze (version 4.2.0)

olink_ttest: Function which performs a t-test per protein

Description

Performs a Welch 2-sample t-test or paired t-test at confidence level 0.95 for every protein (by OlinkID) for a given grouping variable using stats::t.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 t-test table is arranged by ascending p-values.

Usage

olink_ttest(df, variable, pair_id, ...)

Value

A "tibble" containing the t-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" difference in mean NPX between groups

• Group 1: "numeric" Column is named first level of variable when converted to factor, contains mean NPX for that group

• Group 2: "numeric" Column is named second level of variable when converted to factor, contains mean NPX for that group

• statistic: "named numeric" value of the t-statistic

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

• parameter: "named numeric" degrees of freedom for the t-statistic

• conf.low: "numeric" confidence interval for the mean (lower end)

• conf.high: "numeric" confidence interval for the mean (upper end)

• method: "character" which t-test 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 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 t.test. See ?t.test for more information.

Examples

# \donttest{

library(dplyr)

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

ttest_results <- olink_ttest(df=npx_df,
                             variable = 'Treatment',
                             alternative = 'two.sided')

#Paired t-test
npx_df %>%
   filter(Time %in% c("Baseline","Week.6")) %>%
   olink_ttest(variable = "Time", pair_id = "Subject")
# }