permuteFeatures: Calculate score values by calculating difference between...

In tnaake/apoptosisQuantification: Assessment of apoptosis and necroptosus unsing proteomics

Description

The function permuteFeatures calculates the difference between the mean of marker features (e.g. proteins) and random samples of the feature universe (features in values). The scores will be a relative quantification of the marker features to the universe feature intensities. Samples that undergo apoptosis (or any other contamination) will have different differences than uncontaminated samples.

The output will be a tibble containing the differences in means for the samples and repetitions.

Usage

permuteFeatures(
  values,
  args_fct,
  contamination = c("apoptosis", "necroptosis"),
  seed = 2022
)

Arguments

values	data.frame
args_fct	list of arguments, has to contain the entries n_perm (numeric(1)) and signatures (tibble)
contamination	character(1), either "apoptosis" or "necroptosis"
seed	numeric(1)

Details

The number of repetitions is defined by n_perm.

The function will be called in scoreSamples.

Examples

library(SummarizedExperiment)
f <- system.file("protein_datasets/tanzer2020.RDS", 
    package = "apoptosisQuantification")
tanzer2020 <- readRDS(f)
prot <- assay(tanzer2020) |>
    as.data.frame()

## define a list with paramters
args_fct <- list()
args_fct[["signatures"]] <- readMarkers(type = "apoptosis", fc = 2, n = 1)
args_fct[["n_perm"]] <- 100

## run the function
permuteFeatures(values = prot, args_fct = args_fct, 
    contamination = "apoptosis", seed = 2022)

tnaake/apoptosisQuantification documentation built on Feb. 20, 2022, 5:37 p.m.