DOI: 10.18129/B9.bioc.scone    

This is the development version of scone; for the stable release version, see scone.

Single Cell Overview of Normalized Expression data

Bioconductor version: Development (3.15)

SCONE is an R package for comparing and ranking the performance of different normalization schemes for single-cell RNA-seq and other high-throughput analyses.

Author: Michael Cole <mbeloc at>, Davide Risso <risso.davide at>, Matteo Borella <matteobor94 at>, Chiara Romualdi <chiara.romualdi at>

Maintainer: Davide Risso <risso.davide at>

Citation (from within R, enter citation("scone")):


To install this package, start R (version "4.2") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


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biocViews Coverage, GeneExpression, ImmunoOncology, Normalization, Preprocessing, QualityControl, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version 1.19.0
In Bioconductor since BioC 3.5 (R-3.4) (4.5 years)
License Artistic-2.0
Depends R (>= 3.4), methods, SummarizedExperiment
Imports graphics, stats, utils, aroma.light, BiocParallel, class, cluster, compositions, diptest, edgeR, fpc, gplots, grDevices, hexbin, limma, matrixStats, mixtools, RColorBrewer, boot, rhdf5, RUVSeq, rARPACK, MatrixGenerics, SingleCellExperiment
Suggests BiocStyle, DT, ggplot2, knitr, miniUI, NMF, plotly, reshape2, rmarkdown, scran, scRNAseq, shiny, testthat, visNetwork, doParallel, BatchJobs, splatter, scater, kableExtra, mclust, TENxPBMCData
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