Package: MAI
Type: Package
Title: Mechanism-Aware Imputation
Version: 1.16.0
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
Config/pak/sysreqs: libfontconfig1-dev libfreetype6-dev libfribidi-dev
        make libharfbuzz-dev libicu-dev libjpeg-dev libpng-dev
        libtiff-dev libwebp-dev libxml2-dev libssl-dev libx11-dev
        zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2025-10-29 15:11:14 UTC
RemoteUrl: https://github.com/bioc/MAI
RemoteRef: RELEASE_3_22
RemoteSha: e7b90f5697c43d3b16bc7f56c4ed8e5ea3b3ed91
NeedsCompilation: no
Packaged: 2025-11-11 20:35:42 UTC; root
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 4.5.2; ; 2025-11-11 20:38:14 UTC; windows
