olink_ttest {OlinkAnalyze} | R Documentation |
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, ...)
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 |
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)
Examples
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")