Package: LimROTS
Title: LimROTS: A Hybrid Method Integrating Empirical Bayes and
        Reproducibility-Optimized Statistics for Robust Differential
        Expression Analysis
Version: 1.3.25
Authors@R: 
    c(person(given = "Ali", family = "Mostafa Anwar", role = c("aut", "cre"), 
    email= "aliali.mostafa99@gmail.com",
    comment = c(ORCID = "0000-0002-5201-387X")),
    person(given = "Leo", family = "Lahti", role = c("aut" ,"ths"),
    email = "leo.lahti@iki.fi",
    comment = c(ORCID = "0000-0001-5537-637X")),
    person(given = "Akewak", family = "Jeba", role = c("aut","ctb"),
    email = "akewak.k.jeba@utu.fi",
    comment = c(ORCID = "0009-0007-1347-7552")),
    person(given = "Eleanor", family = "Coffey", role = c("aut", "ths"),
    email = "elecof@utu.fi",
    comment = c(ORCID = "0000-0002-9717-5610")),
    person(given = "Rasmus", family = "Hindström", role = "ctb",
    email = "rasmus.hindstrom@utu.fi",
    comment = c(ORCID = "0009-0004-5731-178X")))
Description: 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.
License: GPL (>= 2)
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Depends: R (>= 4.4.0), SummarizedExperiment
biocViews: Software, GeneExpression, DifferentialExpression,
        Microarray, RNASeq, Proteomics, ImmunoOncology, Metabolomics,
        mRNAMicroarray
URL: https://github.com/AliYoussef96/LimROTS,
        https://aliyoussef96.github.io/LimROTS/
BugReports: https://github.com/AliYoussef96/LimROTS/issues
VignetteBuilder: knitr
Imports: limma, stringr, qvalue, utils, stats, BiocParallel, S4Vectors,
        dplyr, survival, cmprsk, variancePartition
Suggests: BiocStyle, ggplot2, testthat (>= 3.0.0), knitr, rmarkdown,
        caret, ROTS, mia, miaTime, TreeSummarizedExperiment
Config/testthat/edition: 3
Config/pak/sysreqs: cmake make libicu-dev zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2026-04-10 13:42:15 UTC
RemoteUrl: https://github.com/bioc/LimROTS
RemoteRef: HEAD
RemoteSha: ab405cbfec563cca7659ebadb4d45b654ba56f8d
NeedsCompilation: no
Packaged: 2026-04-11 06:06:37 UTC; root
Author: Ali Mostafa Anwar [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-5201-387X>),
  Leo Lahti [aut, ths] (ORCID: <https://orcid.org/0000-0001-5537-637X>),
  Akewak Jeba [aut, ctb] (ORCID: <https://orcid.org/0009-0007-1347-7552>),
  Eleanor Coffey [aut, ths] (ORCID:
    <https://orcid.org/0000-0002-9717-5610>),
  Rasmus Hindström [ctb] (ORCID: <https://orcid.org/0009-0004-5731-178X>)
Maintainer: Ali Mostafa Anwar <aliali.mostafa99@gmail.com>
Built: R 4.6.0; ; 2026-04-11 06:10:04 UTC; unix
