FSWE.simExperiment: FSWE.simExperiment

In IFIproteomics/LFQbench: Label Free Quantitation benchmark package

FSWE.simExperiment

Description

This function simulates a complete experiment that can be read by FSWE.

Usage

FSWE.simExperiment(numReplicates, species, speciesRatios, stdDevRatios,
  numProteinsSpecies, peptidesPerProtein, proteinAbundanceDistribution,
  stdDeviationFactorMS, BackgroundSignalLevel, NMARFactor, MARFactor,
  ProteinAbundanceErrorFactor, weibullShape = 0.5)

Arguments

numReplicates	number of replicates of the experiment (same number for samples A and B)
species	vector with species tag names. Example: species = c("HUMAN", "YEAST", "ECOLI")
speciesRatios	vector with expected log ratios for each species. Example: speciesRatios = c(0.0, 1.0, -2.0)
stdDevRatios	biological/prep variation. Example: stdDeviations = c(0.05, 0.1, 0.1)
numProteinsSpecies	vector with number of proteins simulated per species. Example: numProteins = c(2000, 1500, 1000)
peptidesPerProtein	vector with the average number of peptides per protein simulated. Example: peptidesPerProtein = c(10, 8, 5)
proteinAbundanceDistribution	vector containing mean and sd values defining the protein distribution intensities desired. Example: proteinAbundanceDistribution = c(10.0, 5.0)
stdDeviationFactorMS	standard deviation factor (0 to 1) due to MS. Example: stdDeviationFactorMS = 0.03
BackgroundSignalLevel	A threshold value limiting the signal. Every peptide signal estimated under this will be transformed to NA.
NMARFactor	factor of Not Missing At Random missing values in the experiment. They are intensity-dependant!
MARFactor	factor of Missing At Random missing values in the experiment. Taken from a uniform distribution.
ProteinAbundanceErrorFactor	error factor applied to the protein abundance.
weibullShape	shape of the Weibull distribution used to model the probabilities peptides being selected as NMAR value.

IFIproteomics/LFQbench documentation built on March 2, 2023, 9:45 a.m.