LimROTS: A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Differential Expression Analysis

Documentation for package ‘LimROTS’ version 1.3.25

Help Pages

bootstrapS	Generate Bootstrap Samples
bootstrapSamples_limRots	Generate Stratified Bootstrap Samples for limRots
bootstrapSamples_limRots_block	Generate Stratified Bootstrap Samples with Correlation Blocks
bootstrapSamples_limRots_cox	Generate Stratified Bootstrap Samples for Cox limRots with Correlation Blocks
bootstrap_survival	Perform Per-Feature Survival Modeling on Bootstrap Resamples
Boot_parallel	Parallel processing handling function
Boot_parallel_survival	Parallel processing handling function for LimROTS survival
calculateFalseDiscoveryRate	Calculate False Discovery Rate (FDR) Using Permuted Values (Adjusted)
calOverlaps	Calculate Overlaps Between Observed and Permuted Data
calOverlaps_slr	Calculate Overlaps for Single-Label Replicates (SLR)
Check_meta_info	Check if meta info is correct
Check_SummarizedExperiment	Check if SummarizedExperiment or data is correct
countLargerThan	Count Larger Permuted Values (Modified)
fit_survival	Final Per-Feature Survival Model Fit on the Full Dataset
Limma_bootstrap	Perform Linear Modeling with Covariates using Limma
Limma_fit	Perform Linear Modeling with Covariates using Limma
Limma_permutating	Perform Permutation-Based Linear Modeling with Covariates using Limma
LimROTS	'LimROTS': A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Differential Expression Analysis
LimROTS_survival	'LimROTS_survival': A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust survival analysis in Omics Data
Optimizing	Optimize Parameters Based on Overlap Calculations
permutating_survival	Perform Per-Feature Survival Modeling on Permuted Data
SanityChecK	Sanity Check for Input Data and Parameters
UPS1.Case4	Spectronaut and ScaffoldDIA UPS1 Spiked Dataset case 4