R package of techniques for comparing clusterings of single-cell sequencing data
Clone or download

README.md

R package: clusterExperiment

Functions for running and comparing many different clusterings of single-cell sequencing data.

News and Updates

  • Version 2.2.0 will be shortly available on Bioconductor with many new changes. Checkout out a brief description of the major changes. For complete details, see the NEWS file.

  • Summary of changes from previous versions:

Publications

  • The paper acompanying this package can be found at:

    Risso D, Purvis L, Fletcher R, Das D, Ngai J, Dudoit S, Purdom E (2018) "clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets" PLoS Comput Biol. 2018 Sep 4;14(9):e1006378 link

    There is a github repository (epurdom/RSECPaper for this paper that gives the code for reproducing the analysis in that manuscript.

  • A F1000 workflow demonstrating the use of RSEC for clustering as part of trajectory estimation with the package slingshot and normalization with zinbwave

    Perraudeau F, Risso D, Street K, Purdom E, and Dudoit S (2017) "Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference" F1000Research 6:1158.

  • A compiled version of the vignette (i.e. tutorial) of the github version of clusterExperiment (corresponding to the master branch) can be found (here)[http://bioconductor.org/packages/devel/bioc/vignettes/clusterExperiment/inst/doc/clusterExperimentTutorial.html]

  • The compiled version of the vignette corresponding to the version of clusterExperiment available with the latest release of Bioconductor can be found (here)[http://bioconductor.org/packages/release/bioc/vignettes/clusterExperiment/inst/doc/clusterExperimentTutorial.html]

Installation instructions

Installation From Bioconductor

We recommend installation of the package via bioconductor.

if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("clusterExperiment")

To install the most recent version of the package available on the development branch of bioconductor, follow the above instructions, after downloading the development version of bioconductor (see here for instructions).

Installation of Github Version:

We generally try to keep the bioconductor devel version up-to-date with the master branch of this git repository. But since this can require installing R and/or bioconductor development version, it can be convenient to be able to get just the most recent version from github.

You can install the github version via

library(devtools)
install_github("epurdom/clusterExperiment")

Development branch:

The develop branch is our development branch where we are actively updating features, and may contain bugs or be in the process of being updated. You should not use the develop branch unless it passes TravisCI checks (see below) and you want to be using a very beta version.

The development branch can be installed via the install_github command above, but indicating the develop branch:

library(devtools)
install_github("epurdom/clusterExperiment", ref="develop")

Status Checks

Below are status checks for the package. Note that occassionally errors do not appear here immediately. Clicking on the link will give you the most up-to-date status.

Resource: Status
Bioc Release BiocDevel Status
Bioc Development BiocDevel Status
Travis CI master Build Status
Travis CI develop Build Status
Appveyor master AppVeyor Build Status
Appveyor develop AppVeyor Build Status

Issues and bug reports

Please use https://github.com/epurdom/clusterExperiment/issues to submit issues, bug reports, and comments.