impute {DEP} | R Documentation |
impute
imputes missing values in a proteomics dataset.
impute(se, fun = c("bpca", "knn", "QRILC", "MLE", "MinDet", "MinProb", "man", "min", "zero", "mixed", "nbavg"), ...)
se |
SummarizedExperiment,
Proteomics data (output from |
fun |
"bpca", "knn", "QRILC", "MLE", "MinDet",
"MinProb", "man", "min", "zero", "mixed" or "nbavg",
Function used for data imputation based on |
... |
Additional arguments for imputation functions as depicted in
|
An imputed SummarizedExperiment object.
# Load example data <- UbiLength data <- data[data$Reverse != "+" & data$Potential.contaminant != "+",] data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";") # Make SummarizedExperiment columns <- grep("LFQ.", colnames(data_unique)) exp_design <- UbiLength_ExpDesign se <- make_se(data_unique, columns, exp_design) # Filter and normalize filt <- filter_missval(se, thr = 0) norm <- normalize_vsn(filt) # Impute missing values using different functions imputed_MinProb <- impute(norm, fun = "MinProb", q = 0.05) imputed_QRILC <- impute(norm, fun = "QRILC") imputed_knn <- impute(norm, fun = "knn", k = 10, rowmax = 0.9) imputed_MLE <- impute(norm, fun = "MLE") imputed_manual <- impute(norm, fun = "man", shift = 1.8, scale = 0.3)