Name Mode Size
..
appendCeldaList.Rd 100644 1 kb
availableModels.Rd 100644 0 kb
bestLogLikelihood.Rd 100644 1 kb
celda.Rd 100644 0 kb
celdaCGGridSearchRes.Rd 100644 0 kb
celdaCGMod.Rd 100644 0 kb
celdaCGSim.Rd 100644 0 kb
celdaCMod.Rd 100644 0 kb
celdaCSim.Rd 100644 0 kb
celdaClusters.Rd 100644 2 kb
celdaGMod.Rd 100644 0 kb
celdaGSim.Rd 100644 0 kb
celdaGridSearch.Rd 100644 4 kb
celdaHeatmap.Rd 100644 2 kb
celdaModel.Rd 100644 1 kb
celdaModules.Rd 100644 1 kb
celdaPerplexity-celdaList-method.Rd 100644 1 kb
celdaPerplexity.Rd 100644 1 kb
celdaProbabilityMap.Rd 100644 4 kb
celdaTsne.Rd 100644 4 kb
celdaUmap.Rd 100644 4 kb
celda_C.Rd 100644 5 kb
celda_CG.Rd 100644 6 kb
celda_G.Rd 100644 5 kb
celdatosce.Rd 100644 2 kb
clusterProbability.Rd 100644 2 kb
compareCountMatrix.Rd 100644 1 kb
contaminationSim.Rd 100644 0 kb
countChecksum-celdaList-method.Rd 100644 1 kb
countChecksum.Rd 100644 1 kb
decontX.Rd 100644 7 kb
decontXcounts.Rd 100644 1 kb
differentialExpression.Rd 100644 3 kb
distinctColors.Rd 100644 1 kb
eigenMatMultInt.Rd 100644 0 kb
factorizeMatrix.Rd 100644 4 kb
fastNormProp.Rd 100644 0 kb
fastNormPropLog.Rd 100644 0 kb
fastNormPropSqrt.Rd 100644 0 kb
featureModuleLookup.Rd 100644 1 kb
featureModuleTable.Rd 100644 1 kb
findMarkersTree.Rd 100644 6 kb
geneSetEnrich.Rd 100644 2 kb
getDecisions.Rd 100644 1 kb
logLikelihood.Rd 100644 2 kb
logLikelihoodHistory.Rd 100644 1 kb
matrixNames.Rd 100644 1 kb
moduleHeatmap.Rd 100644 7 kb
nonzero.Rd 100644 0 kb
normalizeCounts.Rd 100644 2 kb
params.Rd 100644 1 kb
perplexity.Rd 100644 2 kb
plotCeldaViolin.Rd 100644 2 kb
plotDecontXContamination.Rd 100644 1 kb
plotDecontXMarkerExpression.Rd 100644 3 kb
plotDecontXMarkerPercentage.Rd 100644 4 kb
plotDimReduceCluster.Rd 100644 3 kb
plotDimReduceFeature.Rd 100644 5 kb
plotDimReduceGrid.Rd 100644 4 kb
plotDimReduceModule.Rd 100644 4 kb
plotGridSearchPerplexity.Rd 100644 2 kb
plotGridSearchPerplexityDiff.Rd 100644 2 kb
plotHeatmap.Rd 100644 5 kb
plotMarkerDendro.Rd 100644 2 kb
plotMarkerHeatmap.Rd 100644 2 kb
recodeClusterY.Rd 100644 1 kb
recodeClusterZ.Rd 100644 1 kb
recursiveSplitCell.Rd 100644 7 kb
recursiveSplitModule.Rd 100644 5 kb
resList.Rd 100644 1 kb
resamplePerplexity.Rd 100644 2 kb
retrieveFeatureIndex.Rd 100644 2 kb
runParams.Rd 100644 1 kb
sampleCells.Rd 100644 0 kb
sampleLabel.Rd 100644 2 kb
sceCeldaC.Rd 100644 1 kb
sceCeldaCG.Rd 100644 1 kb
sceCeldaCGGridSearch.Rd 100644 1 kb
sceCeldaG.Rd 100644 1 kb
selectBestModel.Rd 100644 2 kb
selectFeatures.Rd 100644 2 kb
semiPheatmap.Rd 100644 11 kb
simulateCells.Rd 100644 3 kb
simulateContamination.Rd 100644 2 kb
splitModule.Rd 100644 2 kb
subsetCeldaList.Rd 100644 2 kb
topRank.Rd 100644 1 kb
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". 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") ``` To install the development version (R >= 3.6) of **celda** from GitHub using `devtools`: ``` library(devtools) install_github("campbio/celda") ``` **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)