Statistical Methods for Chemoproteomics Dose-Response Analysis

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Documentation for package ‘MSstatsResponse’ version 1.1.2

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

Help Pages

.extractTemplatesFromData	Helper function to extract template profiles from user data
bootstrapIC50	Bootstrap IC50 Estimates and Confidence Interval (ratio scale)
bootstrapIC50LogScale	Bootstrap IC50 Estimates and Confidence Interval (log scale)
bootstrapIC50Precalculated	Bootstrap IC50 with pre-calculated ratios
calculatePeptideWeights	Calculate quality-based weights for peptide measurements
calculateTurnoverRatios	Calculate turnover ratios from MSstats FeatureLevelData
convertGroupToNumericDose	Convert MSstats GROUP labels to numeric dose in nM and extract drug name
DIA_MSstats_Normalized	Example pre-processed DIA-MS dataset
doseResponseFit	Drug-protein interaction detection tested by F-test (fitted curve vs average response)
fitIsotonicRegression	Fit Isotonic Regression Model
futureExperimentSimulation	Test future experimental design using simulated data with user-defined or default templates
MSstatsPrepareDoseResponseFit	Prepare data for dose-response fitting with isotonic regression
plotHitRateMSstatsResponse	Plot hit rates by category
plotIsotonic	Plot Isotonic Regression Model
plot_tpr_power_curve	Visualize detection power across experimental designs
predictIC50	Predict IC50 (dose where response = target) for each protein and drug
predictIC50Parallel	Parallel version of predictIC50 function
run_tpr_simulation	Simulate detection power across experimental design configurations
simulateChemoProteinLevelNonParametric	Simulate chemoproteomics data at the protein level - non-parametric approach
visualizeResponseProtein	Plot isotonic regression fit with optional IC50 for a single protein and drug