https://github.com/krasnitzlab/scclust
Segmentation and Clustering of Single Cell Sequencing Copy Number Profiles
https://github.com/krasnitzlab/scclust
clustering r segmentation single-cell-genomics
Last synced: 2 months ago
JSON representation
Segmentation and Clustering of Single Cell Sequencing Copy Number Profiles
- Host: GitHub
- URL: https://github.com/krasnitzlab/scclust
- Owner: KrasnitzLab
- License: mit
- Created: 2017-10-11T13:27:51.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2022-08-01T18:43:13.000Z (almost 3 years ago)
- Last Synced: 2024-05-09T07:53:06.009Z (about 1 year ago)
- Topics: clustering, r, segmentation, single-cell-genomics
- Language: R
- Homepage:
- Size: 4.01 MB
- Stars: 0
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# SCclust R package
[](https://zenodo.org/badge/latestdoi/106557810)
The SCclust package implements feature selection based on
breakpoints, permutations for FDRs for Fisher test p-values and identification
of the clone structure in single cell copy number profiles.
Threre are two alternative ways to install SCclust package:
* installation from source;
* intallation as a conda package.
## Installation from source
* Download `SCclust` source package from Github:
[https://github.com/KrasnitzLab/SCclust/archive/refs/tags/1.0.7.tar.gz](https://github.com/KrasnitzLab/SCclust/archive/refs/tags/1.0.7.tar.gz)
into your working directory;
* Run `R` and install the package from downloaded source:
```
install.packages("SCclust-1.0.7.tar.gz")
```
## Conda installer
* The `SCclust` package can also be installed using KrasnitzLab Anaconda channel. First create a new conda environment:
```
conda create -n scclust
conda activate scclust
```
and after that install `SCclust` inside it:
```
conda install -c bioconda -c conda-forge -c krasnitzlab scclust
```