MSstatsGroupComparison: Group comparison

In MeenaChoi/MSstats: Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments

Group comparison

Description

Group comparison

Usage

MSstatsGroupComparison(
  summarized_list,
  contrast_matrix,
  save_fitted_models,
  repeated,
  samples_info,
  numberOfCores = 1
)

Arguments

summarized_list	output of MSstatsPrepareForGroupComparison
contrast_matrix	contrast matrix
save_fitted_models	if TRUE, fitted models will be included in the output
repeated	logical, output of checkRepeatedDesign function
samples_info	data.table, output of getSamplesInfo function
numberOfCores	Number of cores for parallel processing. When > 1, a logfile named 'MSstats_groupComparison_log_progress.log' is created to track progress. Only works for Linux & Mac OS.

Examples

QuantData <- dataProcess(SRMRawData, use_log_file = FALSE)
group_comparison_input = MSstatsPrepareForGroupComparison(QuantData)
levels(QuantData$ProteinLevelData$GROUP)
comparison <- matrix(c(-1,0,0,0,0,0,1,0,0,0),nrow=1)
row.names(comparison) <- "T7-T1"
groups = levels(QuantData$ProteinLevelData$GROUP)
colnames(comparison) <- groups[order(as.numeric(groups))]
samples_info = getSamplesInfo(QuantData)
repeated = checkRepeatedDesign(QuantData)
group_comparison = MSstatsGroupComparison(group_comparison_input, comparison,
                                          FALSE, repeated, samples_info)
length(group_comparison) # list of length equal to number of proteins
group_comparison[[1]][[1]] # data used to fit linear model
group_comparison[[1]][[2]] # comparison result
group_comparison[[2]][[3]] # NULL, because we set save_fitted_models to FALSE

MeenaChoi/MSstats documentation built on Nov. 10, 2024, 2:43 p.m.