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scGPS

This is the released version of scGPS; for the devel version, see scGPS.

All versions

3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10

A complete analysis of single cell subpopulations, from identifying subpopulations to analysing their relationship (scGPS = single cell Global Predictions of Subpopulation)

DOI: 10.18129/B9.bioc.scGPS

Bioconductor version: Release (3.23)

The package implements two main algorithms to answer two key questions: a SCORE (Stable Clustering at Optimal REsolution) to find subpopulations, followed by scGPS to investigate the relationships between subpopulations.

Author: Quan Nguyen [aut, cre], Michael Thompson [aut], Anne Senabouth [aut]

Maintainer: Quan Nguyen <quan.nguyen at uq.edu.au>

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

Quan Nguyen, Michael Thompson, Anne Senabouth. scGPS: A complete analysis of single cell subpopulations, from identifying subpopulations to analysing their relationship (scGPS = single cell Global Predictions of Subpopulation). doi:10.18129/B9.bioc.scGPS, R package version 1.26.0, https://bioconductor.org/packages/scGPS.

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

Installation

To install this package, start R (version "4.6") and enter:

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

BiocManager::install("scGPS")

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("scGPS")

Details

Package Archives

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