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README.md
[![Build Status](https://travis-ci.org/campbio/celda.svg?branch=master)](https://travis-ci.org/campbio/celda) [![Coverage Status](https://coveralls.io/repos/github/campbio/celda/badge.svg?branch=master)](https://coveralls.io/github/campbio/celda?branch=master) # celda: CEllular Latent Dirichlet Allocation "celda" stands for "**CE**llular **L**atent **D**irichlet **A**llocation", which 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. Celda has advantages over other clustering frameworks: 1. Celda can simultaneously cluster genes into transcriptional states and cells into subpopulations 2. Celda uses count-based Dirichlet-multinomial distributions so no additional normalization is required for 3' DGE single cell RNA-seq 3. These types of models have shown good performance with sparse data. 4. **Celda now includes DecontX, a computational algorithm for decontamination of droplet based scRNA-seq data.** ## Installation Instructions To install the most recent release of celda (R >= 3.6) via devtools: ``` library(devtools) install_github("campbio/celda") ``` For R3.5 users, please install from the R_3_5 branch. This version of celda is identical to the most recent release of celda except it works on R3.5. ``` library(devtools) install_github("campbio/celda@R_3_5") ``` There has recently been a major update to variable/function names in the celda package. For backward compatibility with results (`celda_CG` and `celda_list` objects) generated from older versions of celda, please install from the mirror branch `20190409_master` which is the release before package reformatting: ``` library(devtools) install_github("campbio/celda@20190409_master") ``` **NOTE** On OSX, `devtools::install_github()` requires installation of **libgit2.** This can be installed via homebrew: ``` brew install libgit2 ``` **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) ``` ## Examples and vignettes Uncompiled vignettes are available in the package. Examples of doing single-cell RNA-seq data analysis using celda and DecontX is available in files vignettes/celda-analysis.Rmd and vignettes/DecontX-analysis.Rmd. ## For developers Check out our [Wiki](https://github.com/campbio/celda/wiki) for [coding style guide](https://github.com/campbio/celda/wiki/Celda-Development-Coding-Style-Guide) if you want to contribute!