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https://github.com/campbio/celda
Bayesian Hierarchical Modeling for Clustering Single Cell Genomic Data
https://github.com/campbio/celda
Last synced: 24 days ago
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Bayesian Hierarchical Modeling for Clustering Single Cell Genomic Data
- Host: GitHub
- URL: https://github.com/campbio/celda
- Owner: campbio
- License: mit
- Created: 2018-11-21T22:01:57.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-04-22T12:16:47.000Z (2 months ago)
- Last Synced: 2024-04-22T13:36:38.154Z (2 months ago)
- Language: R
- Homepage: http://bioconductor.org/packages/celda
- Size: 56.8 MB
- Stars: 143
- Watchers: 7
- Forks: 25
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Lists
- awesome_single_cell - celda - [R] - A suite of Bayesian hierarchical models and supporting functions to perform gene and cell clustering for count data generated by scRNA-seq platforms. This algorithm is an extension of the Latent Dirichlet Allocation (LDA) topic modeling framework that has been popular in text mining applications. (Software packages / RNA-seq)
- awesome-single-cell - celda - [R] - A suite of Bayesian hierarchical models and supporting functions to perform gene and cell clustering for count data generated by scRNA-seq platforms. This algorithm is an extension of the Latent Dirichlet Allocation (LDA) topic modeling framework that has been popular in text mining applications. (Software packages / RNA-seq)
README
[](https://github.com/campbio/celda/actions)
[](https://coveralls.io/github/campbio/celda?branch=master)
# celda: CEllular Latent Dirichlet Allocation
"celda" stands for "**CE**llular **L**atent **D**irichlet **A**llocation". It is a suite of Bayesian hierarchical models and supporting functions to perform gene and cell clustering for count data generated by single cell RNA-seq platforms. This algorithm is an extension of the Latent Dirichlet Allocation (LDA) topic modeling framework that has been popular in text mining applications. This package also includes a method called **DecontX** which can be used to estimate and remove contamination in single cell genomic data.
## Installation Instructions
To install the latest stable release of **celda** from [Bioconductor](http://bioconductor.org/packages/celda/) (requires R version >= 3.6):
```
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("celda")
```
The latest stable version of **celda** can be installed from GitHub using `devtools`:
```
library(devtools)
install_github("campbio/celda")
```
The development version of **celda** can also be installed from GitHub using `devtools`:
```
library(devtools)
install_github("campbio/celda@devel")
```
**NOTE** For MAC OSX users, `devtools::install_github()` requires installation of **libgit2.** This can be installed via homebrew:
```
brew install libgit2
```
Also, if you receive installation errors when Rcpp is being installed and compiled, try following the steps outlined here to solve the issue:
https://thecoatlessprofessor.com/programming/cpp/r-compiler-tools-for-rcpp-on-macos/
If you are running R 4.0.0 or later version on MacOS Catalina and you see error `'wchar.h' file not found`, you can try the method in this link:
https://discourse.mc-stan.org/t/dealing-with-catalina-iii/12731/5
If you are trying to install on MacOS in an Apple Silicon computater and you see the following error:
```
ld: warning: directory not found for option '-L/opt/gfortran/lib/gcc/x86_64-apple-darwin20.0/12.2.0'
ld: warning: directory not found for option '-L/opt/gfortran/lib'
ld: library not found for -lgfortran
clang: error: linker command failed with exit code 1 (use -v to see invocation)
make: *** [celda.so] Error 1
ERROR: compilation failed for package ‘celda’
```
You can solve this by downloading and installing the gfortran pkg located [here](https://mac.r-project.org/tools/gfortran-12.2-universal.pkg) and then running the following command:
```
sudo /opt/gfortran/bin/gfortran-update-sdk
```
**NOTE** If you are trying to install **celda** using Rstudio and get this error: `could not find tools necessary to compile a package`, you can try this:
```
options(buildtools.check = function(action) TRUE)
```
## Vignettes and examples
To build the vignettes for Celda and DecontX during installation from GitHub, use the following command:
```
library(devtools)
install_github("campbio/celda", build_vignettes = TRUE)
```
Note that installation may take an extra 5-10 minutes for building of the vignettes. The Celda and DecontX vignettes can then be accessed via the following commands:
```
vignette("celda")
vignette("decontX")
```
## For developers
Check out our [Wiki](https://github.com/campbio/celda/wiki) for developer's guide if you want to contribute!
- [Celda Development Coding Style Guide](https://github.com/campbio/celda/wiki/Celda-Development-Coding-Style-Guide)
- [Celda Development Robust and Efficient Code](https://github.com/campbio/celda/wiki/Celda-Development-Robust-and-Efficient-Code)
- [Celda Development Rstudio configuration](https://github.com/campbio/celda/wiki/Celda-Development-Rstudio-configuration)
- [FAQ on how to use celda](https://github.com/campbio/celda/wiki/FAQ-on-how-to-use-celda)
- [FAQ on package development](https://github.com/campbio/celda/wiki/FAQ-on-package-development)