Missing values imputation from a MSnSet object

This method is a wrapper to the function impute.pa2() adapted to objects of class MSnSet.

Usage

wrapper.impute.pa2(
  obj,
  design,
  q.min = 0,
  q.norm = 3,
  eps = 0,
  distribution = "unif"
)

Arguments

obj

An object of class SummarizedExperiment.

design

xxx

q.min

A quantile value of the observed values allowing defining the maximal value which can be generated. This maximal value is defined by the quantile q.min of the observed values distribution minus eps. Default is 0 (the maximal value is the minimum of observed values minus eps).

q.norm

A quantile value of a normal distribution allowing defining the minimal value which can be generated. Default is 3 (the minimal value is the maximal value minus qn*median(sd(observed values)) where sd is the standard deviation of a row in a condition).

eps

A value allowing defining the maximal value which can be generated. This maximal value is defined by the quantile q.min of the observed values distribution minus eps. Default is 0.

distribution

The type of distribution used. Values are unif (default) or beta.

Value

The object obj which has been imputed

Author

Thomas Burger, Samuel Wieczorek

Examples

if (FALSE) { # \dontrun{
utils::data(Exp1_R25_pept, package = "DaparToolshedData")
obj <- Exp1_R25_pept[seq_len(100)]
design <- design.qf(obj)
obj.imp.pa2 <- wrapper.impute.pa2(obj = obj[[1]], design = design)
} # }