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digitalDLSorteR
View on CRAN: Click
here
Download and install digitalDLSorteR package within the R console
Install from CRAN:
install.packages("digitalDLSorteR")
Install from Github:
library("remotes")
install_github("cran/digitalDLSorteR") Install by package version:
library("remotes")
install_version("digitalDLSorteR", "1.1.0") Attach the package and use:
library("digitalDLSorteR")
Maintained by
Diego Mañanes
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All associated links for this package
First Published: 2021-10-08
Latest Update:
Description:
Deconvolution of bulk RNA-Seq data using context-specific deconvolution models based on Deep Neural Networks using scRNA-Seq data as input. These models are able to make accurate estimates of the cell composition of bulk RNA-Seq samples from the same context using the advances provided by Deep Learning and the meaningful information provided by scRNA-Seq data. See Torroja and Sanchez-Cabo (2019) for more details.
How to cite:
Diego Mañanes (2021). digitalDLSorteR: Deconvolution of Bulk RNA-Seq Data Based on Deep Learning. R package version 1.1.0, https://cran.r-project.org/web/packages/digitalDLSorteR. Accessed 16 Jul. 2026.
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Complete documentation for digitalDLSorteR
Functions, R codes and Examples using
the digitalDLSorteR R package
Some associated functions: DigitalDLSorter-class . DigitalDLSorterDNN-class . ProbMatrixCellTypes-class . ZinbParametersModel-class . barErrorPlot . barPlotCellTypes . blandAltmanLehPlot . bulk.simul . calculateEvalMetrics . cell.names . cell.types . corrExpPredPlot . deconv.data . deconv.results . deconvDigitalDLSorter . deconvDigitalDLSorterObj . digitalDLSorteR . distErrorPlot . estimateZinbwaveParams . features . generateBulkCellMatrix . getProbMatrix . installTFpython . listToDDLS . listToDDLSDNN . loadDeconvData . loadSCProfiles . loadTrainedModelFromH5 . method . model . plotTrainingHistory . plots . preparingToSave . prob.cell.types . prob.matrix . project . saveRDS . saveTrainedModelAsH5 . set.list . set . showProbPlot . simBulkProfiles . simSCProfiles . single.cell.real . single.cell.simul . test.deconv.metrics . test.metrics . test.pred . trainDigitalDLSorterModel . trained.model . training.history . zinb.params . zinbwave.model .
Some associated R codes: AllClasses.R . AllGenerics.R . digitalDLSorteR.R . dnnModel.R . evalMetrics.R . loadData.R . simBulk.R . simSingleCell.R . utils.R . Full digitalDLSorteR package functions and examples
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