Package: RNAmodR.ML
Type: Package
Title: Detecting patterns of post-transcriptional modifications using
        machine learning
Version: 1.8.0
Date: 2020-07-18
Authors@R: c(person("Felix G.M.",
                    "Ernst", 
                    email = "felix.gm.ernst@outlook.com", 
                    role = c("aut", "cre"),
                    comment = c(ORCID = "0000-0001-5064-0928")),
             person("Denis L.J.", 
                    "Lafontaine", 
                    email = "denis.lafontaine@ulb.ac.be", 
                    role = c("ctb")))
Description: RNAmodR.ML extend the functionality of the RNAmodR package and 
    classical detection strategies towards detection through machine learning
    models. RNAmodR.ML provides classes, functions and an example workflow to 
    establish a detection stratedy, which can be packaged.
biocViews: Software, Infrastructure, WorkflowStep, Visualization,
        Sequencing
License: Artistic-2.0
Encoding: UTF-8
LazyData: false
Depends: R (>= 3.6), RNAmodR
Imports: methods, BiocGenerics, S4Vectors, IRanges, GenomicRanges,
        stats, ranger
Suggests: BiocStyle, knitr, rmarkdown, testthat, RNAmodR.Data,
        RNAmodR.AlkAnilineSeq, GenomicFeatures, Rsamtools, rtracklayer,
        keras
Collate: 'RNAmodR.ML.R' 'AllGenerics.R' 'ModifierMLModel-class.R'
        'ModifierML-class.R' 'ModifierML-data.R'
        'ModifierMLkeras-class.R' 'ModifierMLranger-class.R'
        'RNAmodR.ML.example.R' 'utils.R'
RoxygenNote: 7.1.1
VignetteBuilder: knitr
BugReports: https://github.com/FelixErnst/RNAmodR.ML/issues
URL: https://github.com/FelixErnst/RNAmodR.ML
git_url: https://git.bioconductor.org/packages/RNAmodR.ML
git_branch: RELEASE_3_14
git_last_commit: 406eeec
git_last_commit_date: 2021-10-26
Date/Publication: 2021-10-26
NeedsCompilation: no
Packaged: 2021-10-27 03:43:01 UTC; biocbuild
Author: Felix G.M. Ernst [aut, cre] (<https://orcid.org/0000-0001-5064-0928>),
  Denis L.J. Lafontaine [ctb]
Maintainer: Felix G.M. Ernst <felix.gm.ernst@outlook.com>
Built: R 4.1.1; ; 2021-10-27 13:06:03 UTC; windows
