LimROTS

This is the development version of LimROTS; for the stable release version, see LimROTS.

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

Bioconductor version: Development (3.24)

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")):

Installation

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


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("LimROTS")

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

Documentation


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DifferentialExpression, GeneExpression, ImmunoOncology, Metabolomics, Microarray, Proteomics, RNASeq, Software, mRNAMicroarray
Version	1.5.0
In Bioconductor since	BioC 3.21 (R-4.5) (1 year)
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
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Build Report	Build Report

Package Archives

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

Source Package
Windows Binary (x86_64)
macOS Binary (big-sur-x86_64)
macOS Binary (big-sur-arm64)
macOS Binary (sonoma-arm64)
Source Repository	git clone https://git.bioconductor.org/packages/LimROTS
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/LimROTS
Package Short Url	https://bioconductor.org/packages/LimROTS/
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