outlierFind: outlierFind to identify outliers in a matrix using both...

In mooredf22/protlocassign0p1p1: Compute constrained proportional assignments for fractionated protein abundance

Description

outlierFind to identify outliers in a matrix using both scoresMod and boxplotMod

Usage

outlierFind(
  protClass,
  outlierLevel = "peptide",
  numRefCols = 5,
  numDataCols = 9,
  outlierMeth = "boxplot",
  range = 3,
  proba = 0.99,
  eps = eps,
  cpus = 4,
  randomError = TRUE
)

Arguments

protClass	a matrix of protein, peptide identifiers and normalized specific amounts
outlierLevel	peptide for outlier spectra within peptides, or protein for outlier peptides within proteins'
numRefCols	number of columns before Mass Spectrometry data columns
numDataCols	how many columns in MS data
outlierMeth	boxplot (recommended), scores, or none
range	the range parameter used for identifying outliers
proba	probability to exclude outler for scores method
eps	value to add before log2 transfromations (to avoid taking log of zero)
cpus	number of cpus to use for parallel processing
randomError	T if allow it to be random

Value

additional column of indicators of outlier peptides or outlier spectra for a set of proteins or peptides

Examples

set.seed(17356)
eps <- 0.029885209
data(TLN1_test)
flagSpectraBox <- outlierFind(protClass=TLN1_test,
                              outlierLevel="peptide", numRefCols=5, numDataCols=9,
                              outlierMeth="boxplot", range=3, eps=eps,
                              cpus=1, randomError=TRUE)
# examine numbers of spectra that are outliers
table(flagSpectraBox$outlier.num.spectra)

mooredf22/protlocassign0p1p1 documentation built on Feb. 7, 2022, 1:55 a.m.