amRml/DESCRIPTION at main · JRaviLab/amRml · GitHub

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Package: amRml
Title: Machine learning framework to predict AMR across molecular scales | pkg 2 of 3-pkg amR suite
Version: 0.99.0
Authors@R: c(
    person("Janani", "Ravi", , "janani.ravi@cuanschutz.edu", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0001-7443-925X")),
    person("Ethan", "Wolfe", , "ethan.wolfe@cuanschutz.edu", role = "ctb"),
    person("Evan", "Brenner", , "evan.brenner@cuanschutz.edu", role = "ctb"),
    person("Abhirupa", "Ghosh", , "abhirupa.ghosh@cuanschutz.edu", role = "ctb"),
    person("David", "Mayer", , "david.mayer@cuanschutz.edu", role = "ctb"),
    person("Emily", "Boyer", , "emily.boyer@cuanschutz.edu", role = "ctb"),
    person("Charmie", "Vang", , "charmie.vang@cuanschutz.edu", role = "ctb"),
    person("Alexander", "McKim", , "alexander.mckim@cuanschutz.edu", role = "ctb",
           comment = c(ORCID = "0000-0002-7802-7591"))
  )
Description: Comprehensive machine learning (ML) pipeline for predicting antimicrobial
    resistance (AMR) in ESKAPE pathogens across molecular scales (gene, protein,
    domain, structure). Implements logistic regression using tidymodels framework. Supports multi-drug resistance
    (MDR) and cross-resistance predictions with multiple holdout strategies
    (geographic, temporal, species). Includes model evaluation, feature importance
    analysis, cross-scale performance comparison, and functional characterization
    of top features. Designed to work with data from amRdata package and generate
    results for amRviz visualization. Can work independently with example
    ESKAPE pathogen datasets, too.
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
Depends:
    R (>= 4.5.0)
Suggests:
    BiocStyle,
    knitr,
    rmarkdown,
    testthat (>= 3.0.0),
    xgboost
VignetteBuilder: knitr
Config/testthat/edition: 3
Imports:
    arrow,
    BiocParallel,
    ComplexHeatmap,
    DBI,
    dplyr,
    duckdb,
    circlize,
    forcats,
    ggplot2,
    ggrepel,
    ggridges,
    glmnet,
    glue,
    graphics,
    grDevices,
    jsonlite,
    hardhat,
    methods,
    parsnip,
    purrr,
    patchwork,
    RColorBrewer,
    readr,
    recipes,
    rlang,
    rsample,
    scales,
    sgof,
    stats,
    stringr,
    tibble,
    tidyr,
    tune,
    utils,
    withr,
    workflows,
    workflowsets,
    yardstick
biocViews:
    Software,
    Classification,
    Regression,
    StatisticalMethod,
    FeatureExtraction,
    MultipleComparison,
    FunctionalGenomics,
    Genetics,
    Visualization
URL: https://github.com/JRaviLab/amRml
BugReports: https://github.com/JRaviLab/amRml/issues
Config/roxygen2/version: 8.1.0