process {DEP} | R Documentation |
process
performs data processing on a SummarizedExperiment object.
It (1) filters a proteomics dataset based on missing values,
(2) applies variance stabilizing normalization and
(3) imputes eventual remaining missing values.
process(se, thr = 0, fun = c("man", "bpca", "knn", "QRILC", "MLE", "MinDet", "MinProb", "min", "zero", "mixed", "nbavg"), ...)
se |
SummarizedExperiment,
Proteomics data with unique names and identifiers
annotated in 'name' and 'ID' columns.
The appropriate columns and objects can be generated
using the wrapper import functions |
thr |
Integer(1), Sets the threshold for the allowed number of missing values per condition. |
fun |
"man", "bpca", "knn", "QRILC", "MLE", "MinDet",
"MinProb", "min", "zero", "mixed" or "nbavg",
Function used for data imputation based on |
... |
Additional arguments for imputation functions as depicted in
|
A filtered, normalized and imputed SummarizedExperiment object.
# Load datasets data <- UbiLength exp_design <- UbiLength_ExpDesign # Import data se <- import_MaxQuant(data, exp_design) # Process data processed <- process(se)