Package: LimROTS 1.3.25

Ali Mostafa Anwar

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

Differential expression analysis is commonly used to study diverse biological datasets. The reproducibility-optimized test statistic (ROTS) (Elo et al., 2008, <doi:10.1109/tcbb.2007.1078>) uses a modified t-statistic to prioritise features that differ between two or more groups. However, the ROTS Bioconductor implementation (Suomi et al., 2017, <doi:10.1371/journal.pcbi.1005562>) did not accommodate technical or biological covariates. LimROTS (Anwar et al., 2025, <doi:10.1093/bioinformatics/btaf570>) addressed this limitation by combining a reproducibility-optimized test statistic with the limma empirical Bayes approach (Ritchie et al., 2015, <doi:10.1093/nar/gkv007>). This enables the analysis of more complex experimental designs and the incorporation of covariates.

Authors:Ali Mostafa Anwar [aut, cre], Leo Lahti [aut, ths], Akewak Jeba [aut, ctb], Eleanor Coffey [aut, ths], Rasmus HindstrÃķm [ctb]

LimROTS_1.3.25.tar.gz
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LimROTS.pdf |LimROTS.html✨
LimROTS/json (API)
NEWS

# Install 'LimROTS' in R:
install.packages('LimROTS', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/aliyoussef96/limrots/issues

Pkgdown/docs site:https://aliyoussef96.github.io

Datasets:
  • UPS1.Case4 - Spectronaut and ScaffoldDIA UPS1 Spiked Dataset case 4

On BioConductor:LimROTS-1.3.23(bioc 3.23)LimROTS-1.2.8(bioc 3.22)

softwaregeneexpressiondifferentialexpressionmicroarrayrnaseqproteomicsimmunooncologymetabolomicsmrnamicroarray

6.35 score 4 stars 28 scripts 300 downloads 2 exports 105 dependencies

Last updated from:ab405cbfec. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE222
linux-devel-x86_64OK467
source / vignettesOK359
linux-release-x86_64OK420
macos-release-arm64OK213
macos-oldrel-arm64OK246
windows-develOK429
windows-releaseOK395
windows-oldrelOK421
wasm-releaseOK191

Exports:LimROTSLimROTS_survival

Dependencies:abindaodbackportsBHBiobaseBiocGenericsBiocParallelbitopsbootbroomcaToolsclicmprskcodetoolscolorspacecorpcorcowplotcpp11DelayedArrayDerivdoBydplyrEnvStatsfANCOVAfarverforecastformatRfracdifffutile.loggerfutile.optionsgenericsGenomicRangesggplot2gluegplotsgtablegtoolsIRangesisobanditeratorsKernSmoothlabelinglambda.rlatticelifecyclelimmalme4lmerTestlmtestmagrittrMASSMatrixMatrixGenericsmatrixStatsmicrobenchmarkminqamodelrmvtnormnlmenloptrnnetnortestnumDerivpbkrtestpillarpkgconfigplyrpurrrqvalueR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasremaCorreshape2RhpcBLASctlrlangS4ArraysS4VectorsS7scalesSeqinfosnowSparseArraystatmodstringistringrSummarizedExperimentsurvivaltibbletidyrtidyselecttimeDateurcautf8variancePartitionvctrsviridisLitewithrXVectorzoo

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

Rendered fromLimROTS.Rmdusingknitr::rmarkdownon Apr 11 2026.

Last update: 2026-04-05
Started: 2024-09-23

LimROTS: Survival Analysis with Cox and Competing Risks Models

Rendered fromLimROTS_survival.Rmdusingknitr::rmarkdownon Apr 11 2026.

Last update: 2026-04-05
Started: 2026-04-05

Readme and manuals

Help Manual

Help pageTopics
Parallel processing handling functionBoot_parallel
Parallel processing handling function for LimROTS survivalBoot_parallel_survival
Perform Per-Feature Survival Modeling on Bootstrap Resamplesbootstrap_survival
Generate Bootstrap SamplesbootstrapS
Generate Stratified Bootstrap Samples for limRotsbootstrapSamples_limRots
Generate Stratified Bootstrap Samples with Correlation BlocksbootstrapSamples_limRots_block
Generate Stratified Bootstrap Samples for Cox limRots with Correlation BlocksbootstrapSamples_limRots_cox
Calculate False Discovery Rate (FDR) Using Permuted Values (Adjusted)calculateFalseDiscoveryRate
Calculate Overlaps Between Observed and Permuted DatacalOverlaps
Calculate Overlaps for Single-Label Replicates (SLR)calOverlaps_slr
Check if meta info is correctCheck_meta_info
Check if SummarizedExperiment or data is correctCheck_SummarizedExperiment
Count Larger Permuted Values (Modified)countLargerThan
Final Per-Feature Survival Model Fit on the Full Datasetfit_survival
Perform Linear Modeling with Covariates using LimmaLimma_bootstrap
Perform Linear Modeling with Covariates using LimmaLimma_fit
Perform Permutation-Based Linear Modeling with Covariates using LimmaLimma_permutating
'LimROTS': A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Differential Expression AnalysisLimROTS
'LimROTS_survival': A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust survival analysis in Omics DataLimROTS_survival
Optimize Parameters Based on Overlap CalculationsOptimizing
Perform Per-Feature Survival Modeling on Permuted Datapermutating_survival
Sanity Check for Input Data and ParametersSanityChecK
Spectronaut and ScaffoldDIA UPS1 Spiked Dataset case 4UPS1.Case4