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https://github.com/epurdom/clusterExperiment
R package of techniques for comparing clusterings of single-cell sequencing data
https://github.com/epurdom/clusterExperiment
Last synced: 3 days ago
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R package of techniques for comparing clusterings of single-cell sequencing data
- Host: GitHub
- URL: https://github.com/epurdom/clusterExperiment
- Owner: epurdom
- Created: 2015-11-30T19:06:53.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2022-10-11T22:00:37.000Z (about 2 years ago)
- Last Synced: 2023-12-18T03:10:26.112Z (11 months ago)
- Language: R
- Size: 179 MB
- Stars: 36
- Watchers: 4
- Forks: 13
- Open Issues: 53
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-single-cell - clusterExperiment - [R] - Functions for running and comparing many different clusterings of single-cell sequencing data. Meant to work with SCONE and slingshot. (Software packages / RNA-seq)
README
# R package: clusterExperiment
Functions for running and comparing many different clusterings of single-cell sequencing data.
## News and Updates
* Version 2.3.0 is on Bioconductor (development version) with many new changes. Checkout out a [brief description](https://github.com/epurdom/clusterExperiment/blob/master/update2.4.md) of the major changes. For complete details, see the [NEWS](https://github.com/epurdom/clusterExperiment/blob/master/NEWS) file.
* Summary of changes from previous versions:
- Version 2.0.0 [brief description](https://github.com/epurdom/clusterExperiment/blob/master/update2.0.md)
## 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](http://dx.plos.org/10.1371/journal.pcbi.1006378)
There is a github repository ([epurdom/RSECPaper](https://github.com/epurdom/RSECPaper) for this paper that gives the code for reproducing the analysis in that manuscript.
* A [F1000 workflow](https://f1000research.com/articles/6-1158/v1) 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.
```r
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](https://www.bioconductor.org/developers/how-to/useDevel/) for instructions).
If you are having problems installing/updating the package `gsl` from source because your gsl installation is not found, [this answer](https://stackoverflow.com/a/26616008) (and the comment following it) on stackoverflow may be of help.
### 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
```r
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:
```r
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 | [](http://bioconductor.org/checkResults/release/bioc-LATEST/clusterExperiment/)|
| Bioc Development | [](http://bioconductor.org/checkResults/devel/bioc-LATEST/clusterExperiment/)|
| Travis CI master | [](https://travis-ci.org/epurdom/clusterExperiment) |
| Travis CI develop | [](https://travis-ci.org/epurdom/clusterExperiment) |
| Appveyor master | [](https://ci.appveyor.com/project/epurdom/clusterExperiment) |
| Appveyor develop | [](https://ci.appveyor.com/project/epurdom/clusterExperiment) |
## Issues and bug reports
Please use https://github.com/epurdom/clusterExperiment/issues to submit issues, bug reports, and comments.