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 |
celdaCMod | celdaCMod |
celdaCSim | celdaCSim |
celdaGMod | celdaGMod |
celdaGridSearch | Run Celda in parallel with multiple parameters |
celdaGSim | celdaGSim |
celdaHeatmap | Plot celda Heatmap |
celdaHeatmap-method | Heatmap for celda_C |
celdaHeatmap-method | Heatmap for celda_CG |
celdaHeatmap-method | Heatmap for celda_CG |
celdaPerplexity | Get perplexity for every model in a celdaList |
celdaPerplexity-method | Get perplexity for every model in a celdaList |
celdaProbabilityMap | Renders probability and relative expression heatmaps to visualize the relationship between feature modules and cell populations. |
celdaProbabilityMap-method | Probability map for a celda_C model |
celdaProbabilityMap-method | Probability map for a celda_CG model |
celdaTsne | Embeds cells in two dimensions using tSNE based on celda_CG results. |
celdaTsne-method | tSNE for celda_C |
celdaTsne-method | tSNE for celda_CG |
celdaTsne-method | tSNE for celda_G |
celdaUmap | Embeds cells in two dimensions using umap. |
celdaUmap-method | umap for celda_C |
celdaUmap-method | umap for celda_CG |
celdaUmap-method | umap for celda_G |
celda_C | Cell clustering with Celda |
celda_CG | Cell and feature clustering with Celda |
celda_G | Feature clustering with Celda |
clusterProbability | Get cluster probability |
clusterProbability-method | Conditional probabilities for cells in subpopulations from a Celda_C model |
clusterProbability-method | Conditional probabilities for cells and features from a Celda_CG model |
clusterProbability-method | Conditional probabilities for features in modules from a Celda_G model |
clusters | Get clustering outcomes from a celdaModel |
clusters-method | Get clustering outcomes from a celdaModel |
compareCountMatrix | 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 | Decontaminate count matrix |
differentialExpression | Differential expression for cell subpopulations using MAST |
distinctColors | Create a color palette |
eigenMatMultInt | Fast matrix multiplication for double x int |
factorizeMatrix | Generate factorized matrices showing each feature's influence on cell / gene clustering |
factorizeMatrix-method | Matrix factorization for results from celda_C() |
factorizeMatrix-method | Matrix factorization for results from celda_CG |
factorizeMatrix-method | Matrix factorization for results from celda_G |
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 | Lookup the module of a feature |
featureModuleLookup-method | Lookup the module of a feature |
featureModuleLookup-method | Lookup the module of a feature |
featureModuleTable | Outputting a feature module table |
geneSetEnrich | Gene set enrichment |
logLikelihood | Calculate LogLikelihood |
logLikelihoodcelda_C | Calculate Celda_C log likelihood |
logLikelihoodcelda_CG | Calculate Celda_CG log likelihood |
logLikelihoodcelda_G | Calculate Celda_G log likelihood |
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 |
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 from a single celdaModel |
perplexity-method | Calculate the perplexity on new data with a celda_C model |
perplexity-method | Calculate the perplexity on new data with a celda_CG model |
perplexity-method | Calculate the perplexity on new data with a celda_G model |
plotDimReduceCluster | Plotting the cell labels on a dimensionality reduction plot |
plotDimReduceFeature | Plotting feature expression on a dimensionality reduction plot |
plotDimReduceGrid | Mapping the dimensionality reduction plot |
plotDimReduceModule | Plotting the Celda module probability on a dimensionality reduction plot |
plotGridSearchPerplexity | Visualize perplexity of a list of celda models |
plotGridSearchPerplexitycelda_C | Plot perplexity as a function of K from celda_C models |
plotGridSearchPerplexitycelda_CG | Plot perplexity as a function of K and L from celda_CG models |
plotGridSearchPerplexitycelda_G | Plot perplexity as a function of L from a celda_G model |
plotHeatmap | Plots heatmap based on Celda model |
recodeClusterY | Recode feature module clusters |
recodeClusterZ | Recode cell cluster labels |
recursiveSplitCell | Recursive cell splitting |
recursiveSplitModule | Recursive module splitting |
resamplePerplexity | Calculate and visualize perplexity of all models in a celdaList, with count resampling |
resList | Get final celdaModels from a celdaList |
resList-method | Get final celdaModels from a celdaList |
runParams | Get run parameters provided to 'celdaGridSearch()' |
runParams-method | Get run parameters provided to 'celdaGridSearch()' |
sampleCells | sampleCells |
sampleLabel | Get sampleLabels from a celdaModel |
sampleLabel-method | Get sampleLabels from a celdaModel |
selectBestModel | Select best chain within each combination of parameters |
semiPheatmap | A function to draw clustered heatmaps. |
simulateCells | Simulate count data from the celda generative models. |
simulateCellscelda_C | Simulate cells from the celda_C model |
simulateCellscelda_CG | Simulate cells from the celda_CG model |
simulateCellscelda_G | Simulate cells from the celda_G model |
simulateContaminatedMatrix | Simulate contaminated count matrix |
subsetCeldaList | Subset celdaList object from celdaGridSearch |
topRank | Identify features with the highest influence on clustering. |
violinPlot | Feature Expression Violin Plot |