Package: iimi
Title: Identifying Infection with Machine Intelligence
Version: 1.2.1
Authors@R: c(
    person("Haochen", "Ning", , "hning@uvic.ca", role = c("aut")),
    person("Ian", "Boyes", , "ian.boyes@inspection.gc.ca", role = c("aut")),
    person("Ibrahim", "Numanagić", , "inumanag@uvic.ca", role = c("aut"),
    comment = c(ORCID = "0000-0002-2970-7937")),
    person("Michael", "Rott", , "mike.rott@inspection.gc.ca", role = c("aut")),
    person("Li", "Xing", , "lix491@math.usask.ca", role = c("aut"),
    comment = c(ORCID = "0000-0002-4186-7909")),
    person("Xuekui", "Zhang", , "xuekui@uvic.ca", role = c("aut", "cre"), 
    comment = c(ORCID = "0000-0003-4728-2343")))
Description: A novel machine learning method for plant viruses diagnostic using 
    genome sequencing data. This package includes three different machine 
    learning models, random forest, XGBoost, and elastic net, to train and 
    predict mapped genome samples. Mappability profile and unreliable regions 
    are introduced to the algorithm, and users can build a mappability profile 
    from scratch with functions included in the package. Plotting mapped sample 
    coverage information is provided.
Encoding: UTF-8
RoxygenNote: 7.3.1
LazyData: true
VignetteBuilder: knitr
Imports: Biostrings, caret, data.table, dplyr, GenomicAlignments,
        IRanges, mltools, randomForest, Rsamtools, stats, xgboost,
        Rdpack, MTPS, R.utils, stringr
Depends: R (>= 3.5.0)
Suggests: rmarkdown, testthat (>= 3.0.0), httr, knitr
RdMacros: Rdpack
License: MIT + file LICENSE
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2024-11-01 05:53:46 UTC; dsain
Author: Haochen Ning [aut],
  Ian Boyes [aut],
  Ibrahim Numanagić [aut] (<https://orcid.org/0000-0002-2970-7937>),
  Michael Rott [aut],
  Li Xing [aut] (<https://orcid.org/0000-0002-4186-7909>),
  Xuekui Zhang [aut, cre] (<https://orcid.org/0000-0003-4728-2343>)
Maintainer: Xuekui Zhang <xuekui@uvic.ca>
Repository: CRAN
Date/Publication: 2024-11-01 20:10:01 UTC
Built: R 4.5.2; ; 2025-11-15 16:34:46 UTC; windows
