R: Statistical Methods for Chemoproteomics Dose-Response Analysis

# Statistical Methods for Chemoproteomics Dose-Response Analysis

## Documentation for package ‘MSstatsResponse’ version 1.2.0

- 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