LimROTS

This is the released version of LimROTS; for the devel version, see LimROTS.

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

Bioconductor version: Release (3.23)

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

Author: Ali Mostafa Anwar [aut, cre] ORCID: 0000-0002-5201-387X , Leo Lahti [aut, ths] ORCID: 0000-0001-5537-637X , Akewak Jeba [aut, ctb] ORCID: 0009-0007-1347-7552 , Eleanor Coffey [aut, ths] ORCID: 0000-0002-9717-5610 , Rasmus Hindström [ctb] ORCID: 0009-0004-5731-178X

Maintainer: Ali Mostafa Anwar <aliali.mostafa99 at gmail.com>

Citation (from within R, enter citation("LimROTS")):

Seminal Bioconductor project articles:

Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.

Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("LimROTS")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("LimROTS")

LimROTS: Overview and Differential Expression Analysis	HTML	R Script
LimROTS: Survival Analysis with Cox and Competing Risks Models	HTML	R Script
Reference Manual	PDF
NEWS	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DifferentialExpression, GeneExpression, ImmunoOncology, Metabolomics, Microarray, Proteomics, RNASeq, Software, mRNAMicroarray
Version	1.4.0
In Bioconductor since	BioC 3.21 (R-4.5) (1.5 years)
License	GPL (>= 2)
Depends	R (>= 4.5.0), SummarizedExperiment
Imports	limma, stringr, qvalue, utils, stats, BiocParallel, S4Vectors, dplyr, survival, cmprsk, variancePartition
System Requirements
URL	https://github.com/AliYoussef96/LimROTS https://aliyoussef96.github.io/LimROTS/
Bug Reports	https://github.com/AliYoussef96/LimROTS/issues

Suggests	BiocStyle, ggplot2, testthat (>= 3.0.0), knitr, rmarkdown, caret, ROTS, mia, miaTime, TreeSummarizedExperiment
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	LimROTS_1.4.0.tar.gz
Windows Binary (x86_64)	LimROTS_1.4.0.zip
macOS Binary (big-sur-x86_64)	LimROTS_1.4.0.tgz
macOS Binary (sonoma-arm64)	LimROTS_1.4.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/LimROTS
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/LimROTS
Bioc Package Browser	https://code.bioconductor.org/browse/LimROTS/
Package Short Url	https://bioconductor.org/packages/LimROTS/
Package Downloads Report	Download Stats