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 (3.21)

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 [aut, cph], Davide Risso [aut, cre, cph], Matteo Borella [ctb], Chiara Romualdi [ctb]

Maintainer: Davide Risso <risso.davide at gmail.com>

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

Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("scone")

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("scone")
Introduction to SCONE HTML R Script
PsiNorm normalization HTML R Script
Reference Manual PDF

Details

biocViews Coverage, GeneExpression, ImmunoOncology, Normalization, Preprocessing, QualityControl, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version 1.31.0
In Bioconductor since BioC 3.5 (R-3.4) (7.5 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, DelayedMatrixStats, sparseMatrixStats
System Requirements
URL
Bug Reports https://github.com/YosefLab/scone/issues
See More
Suggests BiocStyle, DT, ggplot2, knitr, miniUI, NMF, plotly, reshape2, rmarkdown, scran, scRNAseq, shiny, testthat, visNetwork, doParallel, batchtools, splatter, scater, kableExtra, mclust, TENxPBMCData
Linking To
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package scone_1.31.0.tar.gz
Windows Binary (x86_64) scone_1.31.0.zip
macOS Binary (x86_64) scone_1.31.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/scone
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scone
Bioc Package Browser https://code.bioconductor.org/browse/scone/
Package Short Url https://bioconductor.org/packages/scone/
Package Downloads Report Download Stats