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scFeatures

scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction


Bioconductor version: Release (3.18)

scFeatures constructs multi-view representations of single-cell and spatial data. scFeatures is a tool that generates multi-view representations of single-cell and spatial data through the construction of a total of 17 feature types. These features can then be used for a variety of analyses using other software in Biocondutor.

Author: Yue Cao [aut, cre], Yingxin Lin [aut], Ellis Patrick [aut], Pengyi Yang [aut], Jean Yee Hwa Yang [aut]

Maintainer: Yue Cao <yue.cao at sydney.edu.au>

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

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("scFeatures")

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("scFeatures")
Overview of scFeatures with case studies HTML R Script
Reference Manual PDF

Details

biocViews CellBasedAssays, SingleCell, Software, Spatial, Transcriptomics
Version 1.3.2
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License GPL-3
Depends R (>= 4.2.0)
Imports DelayedArray, DelayedMatrixStats, EnsDb.Hsapiens.v79, EnsDb.Mmusculus.v79, GSVA, ape, glue, dplyr, ensembldb, gtools, msigdbr, proxyC, reshape2, spatstat.explore, spatstat.geom, tidyr, AUCell, BiocParallel, rmarkdown, methods, stats, cli, SingleCellSignalR, MatrixGenerics, Seurat, DT
System Requirements
URL https://sydneybiox.github.io/scFeatures/ https://github.com/SydneyBioX/scFeatures/
Bug Reports https://github.com/SydneyBioX/scFeatures/issues
See More
Suggests knitr, S4Vectors, survival, survminer, BiocStyle, ClassifyR, org.Hs.eg.db, clusterProfiler
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package scFeatures_1.3.2.tar.gz
Windows Binary scFeatures_1.3.2.zip (64-bit only)
macOS Binary (x86_64) scFeatures_1.3.2.tgz
macOS Binary (arm64) scFeatures_1.3.2.tgz
Source Repository git clone https://git.bioconductor.org/packages/scFeatures
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scFeatures
Bioc Package Browser https://code.bioconductor.org/browse/scFeatures/
Package Short Url https://bioconductor.org/packages/scFeatures/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.18 Source Archive