scone

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 gmail.com>, Davide Risso <risso.davide at gmail.com>, Matteo Borella <matteobor94 at gmail.com>, Chiara Romualdi <chiara.romualdi at gmail.com>

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

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

Installation

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

if (!requireNamespace("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

PDF   Reference Manual

Details

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
LinkingTo
Suggests BiocStyle, DT, ggplot2, knitr, miniUI, NMF, plotly, reshape2, rmarkdown, scran, scRNAseq, shiny, testthat, visNetwork, doParallel, BatchJobs, splatter, scater, kableExtra, mclust, TENxPBMCData
SystemRequirements
Enhances
URL
BugReports https://github.com/YosefLab/scone/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package
Windows Binary
macOS 10.13 (High Sierra)
Source Repository git clone https://git.bioconductor.org/packages/scone
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scone
Package Short Url https://bioconductor.org/packages/scone/
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