dot-missigness_impute_interactions: Compute interaction averages and impute data using mean of...

In wolski/prolfqua: Proteomics Label Free Quantification

Compute interaction averages and impute data using mean of lowest 0.1 (default)

Description

used in Acetylation project p2916

Usage

.missigness_impute_interactions(
  pdata,
  config,
  factors = config$table$factor_keys_depth(),
  probs = 0.1,
  global = TRUE
)

Arguments

pdata	data.frame
config	AnalysisConfiguration
factors	factor to include (default up to factor depth)
probs	quantile to take average from (default 0.1)
global	global min value

Value

function with parameter 'value' 'c("long", "nrReplicates", "nrMeasured", "meanAbundance", "imputed", "allWide", "all")'

function

Examples

istar <- sim_lfq_data_peptide_config(Nprot = 20,weight_missing = 2)
config <- istar$config
analysis <- istar$data
xx <- complete_cases(analysis, config)
nrPepTimesDilution <- length(unique(paste0(xx$protein_Id, xx$peptide_Id))) *
    length(unique(xx$group_))
funx <- .missigness_impute_interactions(xx, config)
long <- funx("long")
alldata <- funx("all")
stopifnot(length(names(alldata)) == 5)

imputed <- funx("imputed")
stopifnot(nrow(imputed) == length(unique(paste0(xx$protein_Id, xx$peptide_Id))))
missing <- funx("nrMeasured")
stopifnot(nrow(missing) == length(unique(paste0(xx$protein_Id, xx$peptide_Id))))

 meanAbundance <- funx("mean")
stopifnot(nrow(meanAbundance) == length(unique(paste0(xx$protein_Id, xx$peptide_Id))))
 stopifnot(sum(is.na(imputed$mean.imp.group_A))==0)

wolski/prolfqua documentation built on April 27, 2024, 4:09 p.m.