# Tools for benchmarking single-cell gene set analysis methods

## Documentation for package ‘GSABenchmark’ version 1.1.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

aggregateRankPlot | Create an aggregate rank plot from a summary object
allBenchmarkPlots | Plot the complete list of benchmark summaries
allBenchmarkResults | Generate all benchmark results with some precomputed arguments. This function generates all benchmark results by using precomputed values for 'normSilDF', 'dimMat' and 'maxDist'.
benchmarkPlots | Plot a list of summary data frames
corrPlots | Create correlation plots for method results
corrSummary | Calculate correlation matrix for method results
efficiencyBenchmark | Extract running times and peak memory usage for gene set analysis methods
geneSetRankPlots | Create gene set rank plots for the method results
mdsPlots | Create MDS plots for method results
memoryPlot | Plot a data frame consisting of gene set analysis method peak memory usage This function plots data frame consisting of method peak memory usages with methods as rows, gene sets and the gene set average as columns.
metricRankPlots | Create metric rank plots for the method results
predJaccardPlots | Create Jaccard tile plots for method binary predictions
ratioPlot | Create a ratio rank plot for the method results
runAddModuleScore | Run AddModuleScore
runAUCell | Run AUCell
runBenchmark | Generate all benchmark results This function performs the entire 'GSABenchmark' pipeline.
runBenchmarkShuffle | Generate all benchmark results for shuffled gene sets This function generates all benchmark results for shuffled gene sets.
runGSAMethods | Run gene set analysis methods
runGSVA | Run GSVA
runJASMINE | Run JASMINE
runMDT | Run MDT using decoupleR
runMethodShuffle | Run gene set analysis method on shuffled gene sets
runMLM | Run MLM using decoupleR
runORA | Run ORA using decoupleR
runPagoda2 | Run pagoda2
runPLAGE | Run PLAGE
runSingscore | Run Singscore
runSiPSiC | Run SiPSiC
runssGSEA | Run ssGSEA
runUCell | Run UCell
runUDT | Run UDT using decoupleR
runVAM | Run VAM
runZscore | Run Zscore
scorePlot | Plot a data frame consisting of gene set analysis method scores This function plots a data frame consisting of method scores with methods as rows, gene sets and the gene set average as columns.
supportedMethods | Show supported methods
timePlot | Plot a data frame consisting of gene set analysis method running times This function plots data frame consisting of method running times with methods as rows, gene sets and the gene set average as columns.