DecontX now lives in the decontX package | Installation | Tutorial | Session Information
Package: celda 1.29.3
Joshua Campbell
celda: CEllular Latent Dirichlet Allocation
Celda is a suite of Bayesian hierarchical models for clustering single-cell RNA-sequencing (scRNA-seq) data. It is able to perform "bi-clustering" and simultaneously cluster genes into gene modules and cells into cell subpopulations. It also provides wrapper functions for DecontX, a Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information, which is implemented in the 'decontX' package. A variety of scRNA-seq data visualization functions is also included.
Authors:
celda_1.29.3.tar.gz
celda_1.29.3.zip(r-4.7-x86_64)celda_1.29.3.zip(r-4.7-arm64)celda_1.29.3.zip(r-4.6-x86_64)celda_1.29.3.zip(r-4.6-arm64)celda_1.29.3.zip(r-4.5-x86_64)
celda_1.29.3.tgz(r-4.6-x86_64)celda_1.29.3.tgz(r-4.6-arm64)celda_1.29.3.tgz(r-4.5-x86_64)celda_1.29.3.tgz(r-4.5-arm64)
celda_1.29.3.tar.gz(r-4.7-arm64)celda_1.29.3.tar.gz(r-4.7-x86_64)celda_1.29.3.tar.gz(r-4.6-arm64)celda_1.29.3.tar.gz(r-4.6-x86_64)
celda_1.29.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
celda/json (API)
| # Install 'celda' in R: |
| install.packages('celda', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/campbio/celda/issues
Datasets:
- celdaCGGridSearchRes - CeldaCGGridSearchRes
- celdaCGMod - CeldaCGmod
- celdaCGSim - CeldaCGSim
- celdaCMod - CeldaCMod
- celdaCSim - CeldaCSim
- celdaGMod - CeldaGMod
- celdaGSim - CeldaGSim
- contaminationSim - ContaminationSim
- sampleCells - SampleCells
- sceCeldaC - SceCeldaC
- sceCeldaCG - SceCeldaCG
- sceCeldaCGGridSearch - SceCeldaCGGridSearch
- sceCeldaG - SceCeldaG
On BioConductor:celda-1.29.0(bioc 3.24)celda-1.28.0(bioc 3.23)
singlecellgeneexpressionclusteringsequencingbayesianimmunooncologydataimportcppopenmp
Last updated from:7dd371780a. Checks:1 WARNING, 15 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 260 | ||
| linux-devel-arm64 | OK | 594 | ||
| linux-devel-x86_64 | OK | 815 | ||
| source / vignettes | OK | 510 | ||
| linux-release-arm64 | OK | 514 | ||
| linux-release-x86_64 | OK | 611 | ||
| macos-release-arm64 | OK | 485 | ||
| macos-release-x86_64 | OK | 664 | ||
| macos-oldrel-arm64 | OK | 369 | ||
| macos-oldrel-x86_64 | OK | 1437 | ||
| windows-devel-arm64 | OK | 651 | ||
| windows-devel-x86_64 | OK | 815 | ||
| windows-release-arm64 | OK | 633 | ||
| windows-release-x86_64 | OK | 802 | ||
| windows-oldrel-x86_64 | OK | 782 | ||
| wasm-release | OK | 260 |
Exports:appendCeldaListavailableModelsbestLogLikelihoodceldacelda_Ccelda_CGcelda_GceldaClustersceldaClusters<-celdaGridSearchceldaHeatmapceldaModelceldaModulesceldaModules<-celdaPerplexityceldaProbabilityMapceldatosceceldaTsneceldaUmapclusterProbabilitycompareCountMatrixcountChecksumdecontXdecontXcountsdecontXcounts<-distinctColorsfactorizeMatrixfeatureModuleLookupfeatureModuleTablefindMarkersTreegeneSetEnrichlogLikelihoodlogLikelihoodHistorymatrixNamesmoduleHeatmapnormalizeCountsparamsperplexityplotCeldaViolinplotDecontXContaminationplotDecontXMarkerExpressionplotDecontXMarkerPercentageplotDendroplotDimReduceClusterplotDimReduceFeatureplotDimReduceGridplotDimReduceModuleplotGridSearchPerplexityplotHeatmapplotMarkerHeatmapplotRPCrecodeClusterYrecodeClusterZrecursiveSplitCellrecursiveSplitModulereorderCeldareportCeldaCGPlotResultsreportCeldaCGRunresamplePerplexityresListretrieveFeatureIndexrunParamssampleLabelsampleLabel<-selectBestModelselectFeaturessimulateCellssimulateContaminationsplitModulesubsetCeldaListtopRank
Dependencies:abindaskpassBHBiobaseBiocGenericscirclizecliclueclustercodetoolscolorspaceComplexHeatmapcpp11crayoncurldata.tabledbscanDelayedArraydendextenddigestdoParalleldqrngenrichRfarverFNNforeachgenericsGenomicRangesGetoptLongggdendroggplot2ggrepelGlobalOptionsgluegridExtragtablehttrIRangesirlbaisobanditeratorsjsonlitelabelinglatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmimeopensslplyrpngpROCR6RColorBrewerRcppRcppAnnoyRcppEigenRcppProgressreshape2rjsonrlangRSpectraRtsneS4ArraysS4VectorsS7scalesSeqinfoshapeSingleCellExperimentsitmoSparseArraystringistringrSummarizedExperimentsysuwotvctrsviridisviridisLitewithrWriteXLSXVector
DecontX has moved to the decontX package
Last update: 2026-10-09
Started: 2020-03-16
Analysis of single-cell genomic data with celda
Introduction | Installation | Generation of a simulated single cell dataset | Feature selection | Performing bi-clustering with celda | Visualization | Plotting cell populations on 2D-embeddings | Creating an expression heatmap | Displaying relationships between modules and cell populations | Examining co-expression with module heatmaps | Identifying reasonable numbers of feature modules and cell subpopulations | Using recursive splitting | Using a grid search | Miscellaneous utility functions | Finding the modules for feature with featureModuleLookup | Reordering cluster labels with recodeClusterZ, recodeClusterY | Session Information
Last update: 2026-09-25
Started: 2020-03-16
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Append two celdaList objects | appendCeldaList |
| available models | availableModels |
| Get the log-likelihood | bestLogLikelihood bestLogLikelihood,celdaModel-method bestLogLikelihood,SingleCellExperiment-method |
| Celda models | celda |
| Cell clustering with Celda | celda_C celda_C,ANY-method celda_C,SingleCellExperiment-method |
| Cell and feature clustering with Celda | celda_CG celda_CG,ANY-method celda_CG,SingleCellExperiment-method |
| Feature clustering with Celda | celda_G celda_G,ANY-method celda_G,SingleCellExperiment-method |
| celdaCGGridSearchRes | celdaCGGridSearchRes |
| celdaCGmod | celdaCGMod |
| celdaCGSim | celdaCGSim |
| Get or set the cell cluster labels from a celda SingleCellExperiment object or celda model object. | celdaClusters celdaClusters,celdaModel-method celdaClusters,SingleCellExperiment-method celdaClusters<- celdaClusters<-,SingleCellExperiment-method |
| celdaCMod | celdaCMod |
| celdaCSim | celdaCSim |
| celdaGMod | celdaGMod |
| Run Celda in parallel with multiple parameters | celdaGridSearch celdaGridSearch,matrix-method celdaGridSearch,SingleCellExperiment-method |
| celdaGSim | celdaGSim |
| Plot celda Heatmap | celdaHeatmap celdaHeatmap,SingleCellExperiment-method |
| Get celda model from a celda SingleCellExperiment object | celdaModel celdaModel,SingleCellExperiment-method |
| Get or set the feature module labels from a celda SingleCellExperiment object. | celdaModules celdaModules,SingleCellExperiment-method celdaModules<- celdaModules<-,SingleCellExperiment-method |
| Get perplexity for every model in a celdaList | celdaPerplexity |
| Get perplexity for every model in a celdaList | celdaPerplexity,celdaList-method |
| Probability map for a celda model | celdaProbabilityMap celdaProbabilityMap,SingleCellExperiment-method |
| Convert old celda model object to 'SCE' object | celdatosce celdatosce,celdaList-method celdatosce,celda_C-method celdatosce,celda_CG-method celdatosce,celda_G-method |
| t-Distributed Stochastic Neighbor Embedding (t-SNE) dimension reduction for celda 'sce' object | celdaTsne celdaTsne,SingleCellExperiment-method |
| Uniform Manifold Approximation and Projection (UMAP) dimension reduction for celda 'sce' object | celdaUmap celdaUmap,SingleCellExperiment-method |
| Get the conditional probabilities of cell in subpopulations from celda model | clusterProbability clusterProbability,SingleCellExperiment-method |
| Check count matrix consistency | compareCountMatrix compareCountMatrix,ANY,celdaList-method compareCountMatrix,ANY,celdaModel-method |
| contaminationSim | contaminationSim |
| Get the MD5 hash of the count matrix from the celdaList | countChecksum |
| Get the MD5 hash of the count matrix from the celdaList | countChecksum,celdaList-method |
| Contamination estimation with decontX | decontX decontX,ANY-method decontX,SingleCellExperiment-method |
| Get or set decontaminated counts matrix | decontXcounts decontXcounts,SingleCellExperiment-method decontXcounts<- decontXcounts<-,SingleCellExperiment-method |
| Create a color palette | distinctColors |
| Fast matrix multiplication for double x int | eigenMatMultInt |
| Fast matrix multiplication for double x double | eigenMatMultNumeric |
| Generate factorized matrices showing each feature's influence on cell / gene clustering | factorizeMatrix factorizeMatrix,ANY,celda_C-method factorizeMatrix,ANY,celda_CG-method factorizeMatrix,ANY,celda_G-method factorizeMatrix,SingleCellExperiment,ANY-method |
| Fast normalization for numeric matrix | fastNormProp |
| Fast normalization for numeric matrix | fastNormPropLog |
| Fast normalization for numeric matrix | fastNormPropSqrt |
| Obtain the gene module of a gene of interest | featureModuleLookup featureModuleLookup,SingleCellExperiment-method |
| Output a feature module table | featureModuleTable |
| Generate marker decision tree from single-cell clustering output | findMarkersTree |
| Gene set enrichment | geneSetEnrich geneSetEnrich,matrix-method geneSetEnrich,SingleCellExperiment-method |
| Gets cluster estimates using rules generated by `celda::findMarkersTree` | getDecisions |
| Calculate the Log-likelihood of a celda model | logLikelihood logLikelihood,matrix,celda_C-method logLikelihood,matrix,celda_CG-method logLikelihood,matrix,celda_G-method logLikelihood,SingleCellExperiment,ANY-method |
| Get log-likelihood history | logLikelihoodHistory logLikelihoodHistory,celdaModel-method logLikelihoodHistory,SingleCellExperiment-method |
| Get feature, cell and sample names from a celdaModel | matrixNames matrixNames,celdaModel-method |
| Heatmap for featureModules | moduleHeatmap moduleHeatmap,SingleCellExperiment-method |
| get row and column indices of none zero elements in the matrix | nonzero |
| Normalization of count data | normalizeCounts |
| Get parameter values provided for celdaModel creation | params params,celdaModel-method |
| Calculate the perplexity of a celda model | perplexity perplexity,ANY,celda_C-method perplexity,ANY,celda_CG-method perplexity,ANY,celda_G-method perplexity,SingleCellExperiment,ANY-method |
| Feature Expression Violin Plot | plotCeldaViolin plotCeldaViolin,ANY-method plotCeldaViolin,SingleCellExperiment-method |
| Plots contamination on UMAP coordinates | plotDecontXContamination |
| Plots expression of marker genes before and after decontamination | plotDecontXMarkerExpression |
| Plots percentage of cells cell types expressing markers | plotDecontXMarkerPercentage |
| Plots dendrogram of _findMarkersTree_ output | plotDendro |
| Plotting the cell labels on a dimension reduction plot | plotDimReduceCluster plotDimReduceCluster,SingleCellExperiment-method plotDimReduceCluster,vector-method |
| Plotting feature expression on a dimension reduction plot | plotDimReduceFeature plotDimReduceFeature,ANY-method plotDimReduceFeature,SingleCellExperiment-method |
| Mapping the dimension reduction plot | plotDimReduceGrid plotDimReduceGrid,ANY-method plotDimReduceGrid,SingleCellExperiment-method |
| Plotting Celda module probability on a dimension reduction plot | plotDimReduceModule plotDimReduceModule,ANY-method plotDimReduceModule,SingleCellExperiment-method |
| Visualize perplexity of a list of celda models | plotGridSearchPerplexity plotGridSearchPerplexity,celdaList-method plotGridSearchPerplexity,SingleCellExperiment-method |
| Plots heatmap based on Celda model | plotHeatmap |
| Generate heatmap for a marker decision tree | plotMarkerHeatmap |
| Visualize perplexity differences of a list of celda models | plotRPC plotRPC,celdaList-method plotRPC,SingleCellExperiment-method |
| Recode feature module labels | recodeClusterY |
| Recode cell cluster labels | recodeClusterZ |
| Recursive cell splitting | recursiveSplitCell recursiveSplitCell,matrix-method recursiveSplitCell,SingleCellExperiment-method |
| Recursive module splitting | recursiveSplitModule recursiveSplitModule,matrix-method recursiveSplitModule,SingleCellExperiment-method |
| Reorder cells populations and/or features modules using hierarchical clustering | reorderCelda reorderCelda,matrix,celda_C-method reorderCelda,matrix,celda_CG-method reorderCelda,matrix,celda_G-method reorderCelda,SingleCellExperiment,ANY-method |
| Generate an HTML report for celda_CG | reportceldaCG reportCeldaCGPlotResults reportCeldaCGRun |
| Calculate and visualize perplexity of all models in a celdaList | resamplePerplexity resamplePerplexity,ANY-method resamplePerplexity,SingleCellExperiment-method |
| Get final celdaModels from a celda model 'SCE' or celdaList object | resList resList,celdaList-method resList,SingleCellExperiment-method |
| Retrieve row index for a set of features | retrieveFeatureIndex |
| Get run parameters from a celda model 'SingleCellExperiment' or 'celdaList' object | runParams runParams,celdaList-method runParams,SingleCellExperiment-method |
| sampleCells | sampleCells |
| Get or set sample labels from a celda SingleCellExperiment object | sampleLabel sampleLabel,celdaModel-method sampleLabel,SingleCellExperiment-method sampleLabel<- sampleLabel<-,SingleCellExperiment-method |
| sceCeldaC | sceCeldaC |
| sceCeldaCG | sceCeldaCG |
| sceCeldaCGGridSearch | sceCeldaCGGridSearch |
| sceCeldaG | sceCeldaG |
| Select best chain within each combination of parameters | selectBestModel selectBestModel,celdaList-method selectBestModel,SingleCellExperiment-method |
| Simple feature selection by feature counts | selectFeatures selectFeatures,matrix-method selectFeatures,SingleCellExperiment-method |
| A function to draw clustered heatmaps. | semiPheatmap |
| Simulate count data from the celda generative models. | simulateCells |
| Simulate contaminated count matrix | simulateContamination |
| Split celda feature module | splitModule splitModule,SingleCellExperiment-method |
| Subset celda model from SCE object returned from 'celdaGridSearch' | subsetCeldaList subsetCeldaList,celdaList-method subsetCeldaList,SingleCellExperiment-method |
| Identify features with the highest influence on clustering. | topRank |
