Aggregation of quantitative data with redistribution of shared peptides

This function aggregate quantitative data using a method of redistribution of shared peptides. Intensity of shared peptides are redistributed proportionally to each protein. Note that the function assumes that the intensities are not log-transformed.

Usage

inner.aggregate.iter(
  pepData,
  X,
  init.method = "Mean",
  method = "Mean",
  n = NULL,
  uniqueiter = FALSE,
  topn_fun = "Mean",
  max_iter = 500
)

Arguments

pepData: A matrix containing the peptide intensities.
X: A matrix acting as an adjacency matrix.
init.method: A function used for initializing the aggregation. Available functions are Sum, Mean, Median, medianPolish or robustSummary. See below for details.
method: A function used for the aggregation. Available functions are Sum, Mean, Median, medianPolish or robustSummary. See below for details.
n: A numeric(1) specifying the number of peptides to use for each protein. If NULL, all peptides are considered.
uniqueiter: A bole
topn_fun: A function used to determine how to choose the top n peptides. Available functions are Sum, Mean or Median. See below for details.
max_iter: A numeric(1) setting the maximum number of iteration.

Value

A matrix containing the aggregated values.

Details

Available functions are :

Sum : base::rowSums()
Mean : base::rowMeans()
Median : matrixStats::rowMedians()
medianPolish : MsCoreUtils::medianPolish(), not available for topn_fun. Note that this method takes significantly more time than the others, and is parallelized to be more efficient.
robustSummary : MsCoreUtils::robustSummary(), not available for topn_fun. Note that this method takes significantly more time than the others, and is parallelized to be more efficient.

Author

Samuel Wieczorek, Manon Gaudin

Examples

if (FALSE) { # \dontrun{
data(Exp1_R25_pept, package="DaparToolshedData")
obj <- Exp1_R25_pept[seq_len(10)]
X <- BuildAdjacencyMatrix(obj[[length(obj)]])
qdata.agg <- inner.aggregate.iter(assay(obj[[length(obj)]]), X)
} # }