Package: ADImpute
Type: Package
Title: Adaptive Dropout Imputer (ADImpute)
Version: 1.21.0
Description: Single-cell RNA sequencing (scRNA-seq) methods are typically unable
    to quantify the expression levels of all genes in a cell, creating a need
    for the computational prediction of missing values (‘dropout imputation’).
    Most existing dropout imputation methods are limited in the sense that they
    exclusively use the scRNA-seq dataset at hand and do not exploit external
    gene-gene relationship information. Here we propose two novel methods: a
    gene regulatory network-based approach using gene-gene relationships learnt
    from external data and a baseline approach corresponding to a sample-wide
    average. ADImpute can implement these novel methods and also combine them
    with existing imputation methods (currently supported: DrImpute, SAVER).
    ADImpute can learn the best performing method per gene and combine the
    results from different methods into an ensemble.
Authors@R: person("Ana Carolina", "Leote", email = "anacarolinaleote@gmail.com",
           role = c("cre","aut"), comment = c(ORCID = "0000-0003-0879-328X"))
License: GPL-3 + file LICENSE
Encoding: UTF-8
LazyData: true
Depends:
    R (>= 4.0)
Imports:
    checkmate,
    BiocParallel,
    data.table,
    DrImpute,
    kernlab,
    MASS,
    Matrix,
    methods,
    rsvd,
    S4Vectors,
    SAVER,
    SingleCellExperiment,
    stats,
    SummarizedExperiment,
    utils
Suggests: 
    BiocStyle,
    knitr,
    rmarkdown,
    testthat
biocViews:
    GeneExpression,
    Network,
    Preprocessing,
    Sequencing,
    SingleCell,
    Transcriptomics
RoxygenNote: 7.1.1
VignetteBuilder: knitr
BugReports: https://github.com/anacarolinaleote/ADImpute/issues
git_url: https://git.bioconductor.org/packages/ADImpute
git_branch: devel
git_last_commit: 8a9fa73
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
