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scone

Single Cell Overview of Normalized Expression data

Bioconductor version: 3.23 · Package version: 1.36.0

Other Bioconductor versions

devel is the development version; release is the current stable one.

3.24 (devel), 3.23 (release)

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.

DOI: 10.18129/B9.bioc.scone

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("scone")

Details

MaintainerDavide Risso <risso.davide@gmail.com>
AuthorMichael Cole [aut, cph], Davide Risso [aut, cre, cph], Matteo Borella [ctb], Chiara Romualdi [ctb]
LicenseArtistic-2.0
Bug Reportshttps://github.com/YosefLab/scone/issues
Source branchRELEASE_3_23
Build report Bioconductor build system, r-universe
biocViewsCoverage, GeneExpression, ImmunoOncology, Normalization, Preprocessing, QualityControl, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Package Short Url https://bioconductor.org/packages/scone/

Citation

From within R, enter citation("scone"):

Michael Cole, Davide Risso. scone: Single Cell Overview of Normalized Expression data. doi:10.18129/B9.bioc.scone, R package version 1.36.0, https://bioconductor.org/packages/scone.

Generated from the package metadata; it may differ from the package's own citation.

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagescone_1.36.0.tar.gz
Windows binary (x86_64)scone_1.36.0.zip
macOS binary (arm64)scone_1.36.0.tgz
macOS binary (x86_64)scone_1.36.0.tgz
Dependencies

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, DelayedMatrixStats, sparseMatrixStats, SparseArray (>= 1.7.6)

Suggests: BiocStyle, DT, ggplot2, knitr, miniUI, NMF, plotly, reshape2, rmarkdown, scran, scRNAseq, shiny, testthat, DelayedArray, visNetwork, doParallel, batchtools, splatter, scater, kableExtra, mclust, TENxPBMCData