View source: R/groupComparison.R
MSstatsGroupComparison | R Documentation |
Group comparison
MSstatsGroupComparison(
summarized_list,
contrast_matrix,
save_fitted_models,
repeated,
samples_info,
numberOfCores = 1
)
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. |
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
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