singscore

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

Rank-based single-sample gene set scoring method

Bioconductor version: Development (3.21)

A simple single-sample gene signature scoring method that uses rank-based statistics to analyze the sample's gene expression profile. It scores the expression activities of gene sets at a single-sample level.

Author: Dharmesh D. Bhuva [aut] (ORCID: ), Ruqian Lyu [aut, ctb], Momeneh Foroutan [aut, ctb] (ORCID: ), Malvika Kharbanda [aut, cre] (ORCID: )

Maintainer: Malvika Kharbanda <kharbanda.m at wehi.edu.au>

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

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("singscore")

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("singscore")

Single sample scoring	HTML	R Script
Reference Manual	PDF
NEWS	Text

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	GeneExpression, GeneSetEnrichment, Software
Version	1.27.0
In Bioconductor since	BioC 3.7 (R-3.5) (6.5 years)
License	GPL-3
Depends	R (>= 3.6)
Imports	methods, stats, graphics, ggplot2, grDevices, ggrepel, GSEABase, plotly, tidyr, plyr, magrittr, reshape, edgeR, RColorBrewer, Biobase, BiocParallel, SummarizedExperiment, matrixStats, reshape2, S4Vectors
System Requirements
URL	https://davislaboratory.github.io/singscore
Bug Reports	https://github.com/DavisLaboratory/singscore/issues

Suggests	pkgdown, BiocStyle, hexbin, knitr, rmarkdown, testthat, covr
Linking To
Enhances
Depends On Me
Imports Me	SingscoreAMLMutations, clustermole, GSEMA
Suggests Me	mastR, vissE, msigdb
Links To Me
Build Report	Build Report

Package Archives

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

Source Package	singscore_1.27.0.tar.gz
Windows Binary (x86_64)	singscore_1.27.0.zip
macOS Binary (x86_64)	singscore_1.27.0.tgz
macOS Binary (arm64)	singscore_1.27.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/singscore
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/singscore
Bioc Package Browser	https://code.bioconductor.org/browse/singscore/
Package Short Url	https://bioconductor.org/packages/singscore/
Package Downloads Report	Download Stats