Name Mode Size
..
RcppExports.R 100644 4 kb
aaa.R 100644 1 kb
accessors.R 100644 15 kb
celdaGridSearch.R 100755 26 kb
celdaProbabilityMap.R 100644 13 kb
celdaUMAP.R 100644 13 kb
celda_C.R 100755 28 kb
celda_CG.R 100755 31 kb
celda_G.R 100755 24 kb
celda_functions.R 100755 25 kb
celda_heatmap.R 100644 4 kb
celdatSNE.R 100644 10 kb
celdatosce.R 100644 7 kb
clusterProbability.R 100644 7 kb
data.R 100755 4 kb
decon.R 100644 44 kb
elbow.R 100644 1 kb
factorizeMatrix.R 100644 16 kb
featureModuleLookup.R 100644 3 kb
geneSetEnrich.R 100644 5 kb
initialize_clusters.R 100644 10 kb
loglikelihood.R 100644 10 kb
matrixSums.R 100755 4 kb
misc.R 100644 2 kb
moduleHeatmap.R 100644 20 kb
perplexity.R 100644 39 kb
plotHeatmap.R 100644 12 kb
plot_decontx.R 100644 20 kb
plot_dr.R 100755 50 kb
recursiveSplit.R 100644 50 kb
reorderCelda.R 100644 9 kb
reports.R 100644 8 kb
selectFeatures.R 100644 3 kb
semi_pheatmap.R 100755 54 kb
simulateCells.R 100644 18 kb
splitModule.R 100644 5 kb
split_clusters.R 100644 17 kb
topRank.R 100644 3 kb
README.md
<!-- badges: start --> [![R-CMD-check](https://github.com/campbio/celda/workflows/R-CMD-check/badge.svg)](https://github.com/campbio/celda/actions) [![Coverage Status](https://coveralls.io/repos/github/campbio/celda/badge.svg?branch=master)](https://coveralls.io/github/campbio/celda?branch=master) <!-- badges: end --> # 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 **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)