DOI: 10.18129/B9.bioc.ADImpute  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see ADImpute.

Adaptive Dropout Imputer (ADImpute)

Bioconductor version: 3.17

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.

Author: Ana Carolina Leote [cre, aut]

Maintainer: Ana Carolina Leote <anacarolinaleote at>

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biocViews GeneExpression, Network, Preprocessing, Sequencing, SingleCell, Software, Transcriptomics
Version 1.10.0
In Bioconductor since BioC 3.12 (R-4.0) (3 years)
License GPL-3 + file LICENSE
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
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