Package: ADImpute Type: Package Title: Adaptive Dropout Imputer (ADImpute) Version: 1.23.0 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 Config/pak/sysreqs: zlib1g-dev Repository: https://bioc.r-universe.dev Date/Publication: 2026-04-28 12:54:17 UTC RemoteUrl: https://github.com/bioc/ADImpute RemoteRef: HEAD RemoteSha: 1bb2e1c2a794212deb7080ffe9fcee7b2d5a4808 NeedsCompilation: no Packaged: 2026-07-04 01:36:57 UTC; root Author: Ana Carolina Leote [cre, aut] (ORCID: ) Maintainer: Ana Carolina Leote