Package: MAI
Type: Package
Title: Mechanism-Aware Imputation
Version: 1.18.0
Authors@R: 
  c(person(given = "Jonathan",
           family = "Dekermanjian",
           role = c("aut", "cre"),
           email = "Jonathan.Dekermanjian@CUAnschutz.edu"),
    person(given = "Elin",
           family = "Shaddox",
           role = c("aut"),
           email = "Elin.Shaddox@CUAnschutz.edu"),
    person(given = "Debmalya",
           family = "Nandy",
           role = c("aut"),
           email = "Debmalya.Nandy@CUAnschutz.edu"),
   person(given = "Debashis",
           family = "Ghosh",
           role = c("aut"),
           email = "Debashis.Ghosh@CUAnschutz.edu"),
   person(given = "Katerina",
           family = "Kechris",
           role = c("aut"),
           email = "Katerina.Kechris@CUAnschutz.edu"))
Description: A two-step approach to imputing missing data in metabolomics.
    Step 1 uses a random forest classifier to classify missing values as
    either Missing Completely at Random/Missing At Random (MCAR/MAR) or Missing
    Not At Random (MNAR). MCAR/MAR are combined because it is often difficult to
    distinguish these two missing types in metabolomics data. Step 2 imputes the
    missing values based on the classified missing mechanisms, using the
    appropriate imputation algorithms. Imputation algorithms tested and
    available for MCAR/MAR include Bayesian Principal Component Analysis (BPCA),
    Multiple Imputation No-Skip K-Nearest Neighbors (Multi_nsKNN), and
    Random Forest. Imputation algorithms tested and available for MNAR include
    nsKNN and a single imputation approach for imputation of metabolites where
    left-censoring is present.
License: GPL-3
Encoding: UTF-8
Imports: caret, parallel, doParallel, foreach, e1071, future.apply,
        future, missForest, pcaMethods, tidyverse, stats, utils,
        methods, SummarizedExperiment, S4Vectors
biocViews: Software, Metabolomics, StatisticalMethod, Classification
Suggests: knitr, rmarkdown, BiocStyle, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://github.com/KechrisLab/MAI
BugReports: https://github.com/KechrisLab/MAI/issues
git_url: https://git.bioconductor.org/packages/MAI
git_branch: RELEASE_3_23
git_last_commit: e6eb810
git_last_commit_date: 2026-04-28
Repository: Bioconductor 3.23
Date/Publication: 2026-04-28
NeedsCompilation: no
Packaged: 2026-04-28 22:40:46 UTC; biocbuild
Author: Jonathan Dekermanjian [aut, cre],
  Elin Shaddox [aut],
  Debmalya Nandy [aut],
  Debashis Ghosh [aut],
  Katerina Kechris [aut]
Maintainer: Jonathan Dekermanjian <Jonathan.Dekermanjian@CUAnschutz.edu>
Depends: R (>= 3.5.0)
Built: R 4.6.0; ; 2026-04-29 04:48:44 UTC; unix
