Bioconductor / Contributions

Contribute Packages to Bioconductor
134 stars 33 forks source link

LimROTS #3599

Open AliYoussef96 opened 2 hours ago

AliYoussef96 commented 2 hours ago

Update the following URL to point to the GitHub repository of the package you wish to submit to Bioconductor

Confirm the following by editing each check box to '[x]'

I am familiar with the essential aspects of Bioconductor software management, including:

For questions/help about the submission process, including questions about the output of the automatic reports generated by the SPB (Single Package Builder), please use the #package-submission channel of our Community Slack. Follow the link on the home page of the Bioconductor website to sign up.

bioc-issue-bot commented 2 hours ago

Hi @AliYoussef96

Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.

The DESCRIPTION file for this package is:

Package: LimROTS
Title: A Hybrid Method Integrating Empirical Bayes and 
        Reproducibility-Optimized Statistics for Robust Analysis of Proteomics 
        and Metabolomics Data
Version: 0.99.0
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")))
Description: 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.
License: Artistic-2.0
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends: R (>= 4.4.0)
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,
    parallel,
    foreach,
    doParallel,
    stringr,
    qvalue,
    SummarizedExperiment,
    utils,
    stats,
    doRNG,
    dplyr
Suggests: 
    BiocStyle,
    ggplot2,
    magick,
    testthat (>= 3.0.0),
    knitr,
    rmarkdown,
    ROTS
Config/testthat/edition: 3