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 AnalysisBioconductor version: Release (3.21)
Differential expression analysis is a prevalent method utilised in the examination of diverse biological data. The reproducibility-optimized test statistic (ROTS) modifies a t-statistic based on the data's intrinsic characteristics and ranks features according to their statistical significance for differential expression between two or more groups (f-statistic). Focussing on proteomics and metabolomics, the current ROTS implementation cannot account for technical or biological covariates such as MS batches or gender differences among the samples. Consequently, we developed LimROTS, which employs a reproducibility-optimized test statistic utilising the limma methodology to simulate complex experimental designs. LimROTS is a hybrid method integrating empirical bayes and reproducibility-optimized statistics for robust analysis of proteomics and metabolomics data.
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
Maintainer: Ali Mostafa Anwar <aliali.mostafa99 at gmail.com>
Citation (from within R, entercitation("LimROTS")): Installation
To install this package, start R (version "4.5") 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.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("LimROTS")Follow Installation instructions to use this package in your R session.
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