| appendCeldaList | Append two celdaList objects |
| availableModels | available models |
| bestLogLikelihood | Get the log-likelihood |
| bestLogLikelihood-method | Get the log-likelihood |
| celda | Celda models |
| celdaCGGridSearchRes | celdaCGGridSearchRes |
| celdaCGMod | celdaCGmod |
| celdaCGSim | celdaCGSim |
| celdaClusters | Get or set the cell cluster labels from a celda SingleCellExperiment object or celda model object. |
| celdaClusters-method | Get or set the cell cluster labels from a celda SingleCellExperiment object or celda model object. |
| celdaClusters<- | Get or set the cell cluster labels from a celda SingleCellExperiment object or celda model object. |
| celdaClusters<--method | Get or set the cell cluster labels from a celda SingleCellExperiment object or celda model object. |
| celdaCMod | celdaCMod |
| celdaCSim | celdaCSim |
| celdaGMod | celdaGMod |
| celdaGridSearch | Run Celda in parallel with multiple parameters |
| celdaGridSearch-method | Run Celda in parallel with multiple parameters |
| celdaGSim | celdaGSim |
| celdaHeatmap | Plot celda Heatmap |
| celdaHeatmap-method | Plot celda Heatmap |
| celdaModel | Get celda model from a celda SingleCellExperiment object |
| celdaModel-method | Get celda model from a celda SingleCellExperiment object |
| celdaModules | Get or set the feature module labels from a celda SingleCellExperiment object. |
| celdaModules-method | Get or set the feature module labels from a celda SingleCellExperiment object. |
| celdaModules<- | Get or set the feature module labels from a celda SingleCellExperiment object. |
| celdaModules<--method | Get or set the feature module labels from a celda SingleCellExperiment object. |
| celdaPerplexity | Get perplexity for every model in a celdaList |
| celdaPerplexity-method | Get perplexity for every model in a celdaList |
| celdaProbabilityMap | Probability map for a celda model |
| celdaProbabilityMap-method | Probability map for a celda model |
| celdatosce | Convert old celda model object to 'SCE' object |
| celdatosce-method | Convert old celda model object to 'SCE' object |
| celdaTsne | t-Distributed Stochastic Neighbor Embedding (t-SNE) dimension reduction for celda 'sce' object |
| celdaTsne-method | t-Distributed Stochastic Neighbor Embedding (t-SNE) dimension reduction for celda 'sce' object |
| celdaUmap | Uniform Manifold Approximation and Projection (UMAP) dimension reduction for celda 'sce' object |
| celdaUmap-method | Uniform Manifold Approximation and Projection (UMAP) dimension reduction for celda 'sce' object |
| celda_C | Cell clustering with Celda |
| celda_C-method | Cell clustering with Celda |
| celda_CG | Cell and feature clustering with Celda |
| celda_CG-method | Cell and feature clustering with Celda |
| celda_G | Feature clustering with Celda |
| celda_G-method | Feature clustering with Celda |
| clusterProbability | Get the conditional probabilities of cell in subpopulations from celda model |
| clusterProbability-method | Get the conditional probabilities of cell in subpopulations from celda model |
| compareCountMatrix | Check count matrix consistency |
| compareCountMatrix-method | Check count matrix consistency |
| contaminationSim | contaminationSim |
| countChecksum | Get the MD5 hash of the count matrix from the celdaList |
| countChecksum-method | Get the MD5 hash of the count matrix from the celdaList |
| decontX | Contamination estimation with decontX |
| decontX-method | Contamination estimation with decontX |
| decontXcounts | Get or set decontaminated counts matrix |
| decontXcounts-method | Get or set decontaminated counts matrix |
| decontXcounts<- | Get or set decontaminated counts matrix |
| decontXcounts<--method | Get or set decontaminated counts matrix |
| distinctColors | Create a color palette |
| eigenMatMultInt | Fast matrix multiplication for double x int |
| eigenMatMultNumeric | Fast matrix multiplication for double x double |
| factorizeMatrix | Generate factorized matrices showing each feature's influence on cell / gene clustering |
| factorizeMatrix-method | Generate factorized matrices showing each feature's influence on cell / gene clustering |
| fastNormProp | Fast normalization for numeric matrix |
| fastNormPropLog | Fast normalization for numeric matrix |
| fastNormPropSqrt | Fast normalization for numeric matrix |
| featureModuleLookup | Obtain the gene module of a gene of interest |
| featureModuleLookup-method | Obtain the gene module of a gene of interest |
| featureModuleTable | Output a feature module table |
| findMarkersTree | Generate marker decision tree from single-cell clustering output |
| geneSetEnrich | Gene set enrichment |
| geneSetEnrich-method | Gene set enrichment |
| getDecisions | Gets cluster estimates using rules generated by 'celda::findMarkersTree' |
| logLikelihood | Calculate the Log-likelihood of a celda model |
| logLikelihood-method | Calculate the Log-likelihood of a celda model |
| logLikelihoodHistory | Get log-likelihood history |
| logLikelihoodHistory-method | Get log-likelihood history |
| matrixNames | Get feature, cell and sample names from a celdaModel |
| matrixNames-method | Get feature, cell and sample names from a celdaModel |
| moduleHeatmap | Heatmap for featureModules |
| moduleHeatmap-method | Heatmap for featureModules |
| nonzero | get row and column indices of none zero elements in the matrix |
| normalizeCounts | Normalization of count data |
| params | Get parameter values provided for celdaModel creation |
| params-method | Get parameter values provided for celdaModel creation |
| perplexity | Calculate the perplexity of a celda model |
| perplexity-method | Calculate the perplexity of a celda model |
| plotCeldaViolin | Feature Expression Violin Plot |
| plotCeldaViolin-method | Feature Expression Violin Plot |
| plotDecontXContamination | Plots contamination on UMAP coordinates |
| plotDecontXMarkerExpression | Plots expression of marker genes before and after decontamination |
| plotDecontXMarkerPercentage | Plots percentage of cells cell types expressing markers |
| plotDendro | Plots dendrogram of _findMarkersTree_ output |
| plotDimReduceCluster | Plotting the cell labels on a dimension reduction plot |
| plotDimReduceCluster-method | Plotting the cell labels on a dimension reduction plot |
| plotDimReduceFeature | Plotting feature expression on a dimension reduction plot |
| plotDimReduceFeature-method | Plotting feature expression on a dimension reduction plot |
| plotDimReduceGrid | Mapping the dimension reduction plot |
| plotDimReduceGrid-method | Mapping the dimension reduction plot |
| plotDimReduceModule | Plotting Celda module probability on a dimension reduction plot |
| plotDimReduceModule-method | Plotting Celda module probability on a dimension reduction plot |
| plotGridSearchPerplexity | Visualize perplexity of a list of celda models |
| plotGridSearchPerplexity-method | Visualize perplexity of a list of celda models |
| plotHeatmap | Plots heatmap based on Celda model |
| plotMarkerHeatmap | Generate heatmap for a marker decision tree |
| plotRPC | Visualize perplexity differences of a list of celda models |
| plotRPC-method | Visualize perplexity differences of a list of celda models |
| recodeClusterY | Recode feature module labels |
| recodeClusterZ | Recode cell cluster labels |
| recursiveSplitCell | Recursive cell splitting |
| recursiveSplitCell-method | Recursive cell splitting |
| recursiveSplitModule | Recursive module splitting |
| recursiveSplitModule-method | Recursive module splitting |
| reorderCelda | Reorder cells populations and/or features modules using hierarchical clustering |
| reorderCelda-method | Reorder cells populations and/or features modules using hierarchical clustering |
| reportceldaCG | Generate an HTML report for celda_CG |
| reportCeldaCGPlotResults | Generate an HTML report for celda_CG |
| reportCeldaCGRun | Generate an HTML report for celda_CG |
| resamplePerplexity | Calculate and visualize perplexity of all models in a celdaList |
| resamplePerplexity-method | Calculate and visualize perplexity of all models in a celdaList |
| resList | Get final celdaModels from a celda model 'SCE' or celdaList object |
| resList-method | Get final celdaModels from a celda model 'SCE' or celdaList object |
| retrieveFeatureIndex | Retrieve row index for a set of features |
| runParams | Get run parameters from a celda model 'SingleCellExperiment' or 'celdaList' object |
| runParams-method | Get run parameters from a celda model 'SingleCellExperiment' or 'celdaList' object |
| sampleCells | sampleCells |
| sampleLabel | Get or set sample labels from a celda SingleCellExperiment object |
| sampleLabel-method | Get or set sample labels from a celda SingleCellExperiment object |
| sampleLabel<- | Get or set sample labels from a celda SingleCellExperiment object |
| sampleLabel<--method | Get or set sample labels from a celda SingleCellExperiment object |
| sceCeldaC | sceCeldaC |
| sceCeldaCG | sceCeldaCG |
| sceCeldaCGGridSearch | sceCeldaCGGridSearch |
| sceCeldaG | sceCeldaG |
| selectBestModel | Select best chain within each combination of parameters |
| selectBestModel-method | Select best chain within each combination of parameters |
| selectFeatures | Simple feature selection by feature counts |
| selectFeatures-method | Simple feature selection by feature counts |
| semiPheatmap | A function to draw clustered heatmaps. |
| simulateCells | Simulate count data from the celda generative models. |
| simulateContamination | Simulate contaminated count matrix |
| splitModule | Split celda feature module |
| splitModule-method | Split celda feature module |
| subsetCeldaList | Subset celda model from SCE object returned from 'celdaGridSearch' |
| subsetCeldaList-method | Subset celda model from SCE object returned from 'celdaGridSearch' |
| topRank | Identify features with the highest influence on clustering. |