
Package index
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UpdateEnvCache() - Handy
CondaEnvMangerinstance modifier
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resetCache() - Reset a conda environment
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saveToCache() - Save a conda environment manager to cache
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getCache() - Get current cache of conda environments
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getCachePath() - Get path to package config cache
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reloadCache() - Reload cache from disk
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CondaEnv() - Handy
CondaEnvinstance constructor
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CondaManager() - Handy
CondaEnvMangerinstance constructor
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isValid() - Check the validity of conda environment's components
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checkCondaBin()checkCondaEnvPath()checkCondaEnvName()checkCondaEnv() - Check the validity of conda environment's components
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DoIntegrate() - Integrate layers using one or multiple integration method(s)
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CombatIntegration() - Run ComBat on Seurat's Assay5 object through
IntegrateLayers
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HarmonyIntegration()HarmonyIntegration.fix() - Run Harmony on Seurat's Assay5 object through
IntegrateLayers
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MNNIntegration() - Run classical MNN on Seurat's Assay5 object through
IntegrateLayers
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ScanoramaIntegration() - Run Scanorama on Seurat's Assay5 object through
IntegrateLayers
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bbknnIntegration() - Run bbknn on Seurat's Assay5 object through
IntegrateLayers
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scANVIIntegration() - Run scANVI on Seurat's Assay5 object through
IntegrateLayers
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scVIIntegration()scVIIntegration.fix() - Run scVI on Seurat's Assay5 object through
IntegrateLayers
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trVAEIntegration() - Run trVAE on Seurat's Assay5 object through
IntegrateLayers
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RPCAIntegration() - Seurat-RPCA Integration (from Seurat)
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CCAIntegration() - Seurat-CCA Integration (from Seurat)
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FastMNNIntegration() - Run fastMNN in Seurat 5 (from SeuratWrappers)
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FindOptimalClusters() - Find a clustering that maximises NMI or ARI
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CellCycleScoringPerBatch() - Score cell cycle phases per batch
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ScoreARI()AddScoreARI() - Score a clustering result with adjusted rand index
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ScoreASW()AddScoreASW()ScoreASWBatch()AddScoreASWBatch() - Score an embedding or a count matrix with the average silhouette width
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ScoreRegressPC.CellCycle()AddScoreRegressPC.CellCycle() - Score a corrected or uncorrected PCA to estimate the contribution of S and G2M scores to variance
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ScoreConnectivity()AddScoreConnectivity() - Score a knn graph based on cell-type label connectivity
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ScoreDensityPC()AddScoreDensityPC() - Score a corrected or uncorrected PCA to estimate batch mixing
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ScoreKBET()AddScoreKBET() - Score an embedding or a knn graph with the kBET test
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AddScoreLISI()ScoreLISI() - Score a dimensionality reduction embedding or knn graph using the Local Inverse Simpson Index
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ScoreNMI()AddScoreNMI() - Score a clustering result with normalised mutual information
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ScoreRegressPC()AddScoreRegressPC() - Score a corrected or uncorrected PCA to estimate batch mixing
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ScoreScGraph()AddScoreScGraph() - Score a dimension reduction by correlating normalised centroid distances
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ScaleScores() - Scale the scores in the score tibble to plot them
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PlotScores() - Visualise and compare the performances of integration algorithms
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GetMiscIntegrations()GetMiscScores()IntegrationScores() - Retrieve integration scores from a Seurat object
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SetMiscScore() - Set the value of a score in the score tibble
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AddMiscIntegrations()AddMiscScores() - Add integration(s) or score(s) slot(s) to the score tibble
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SymmetrizeKnn() - Symmetrize a nearest neighbours graph
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CutKnn() - Remove excessive number of neighbours in a knn graph
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ExpandNeighbours() - Expand knn graph to increase the number of neighbours
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GetConnectivities() - Derive connectivities from distances
Connectivity between batches
Handy functions to overview inter- and intra-batches connections in a knn graph
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GetPropInterBatch() - Calculate proportion of nearest neighbours between batches
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GetPropIntraBatch() - Calculate proportion of nearest neighbours within batches
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NormaliseL2() - Normalise a matrix using L2 norm
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rowSort()colSort()rowSorted()colSorted() - Matrix sorting
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symmetrize.pmax.sparse()symmetrize.pmin.sparse() - Matrix symmetrizing
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rowSort()colSort()rowSorted()colSorted() - Matrix sorting
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rowcol2idx()idx2col()idx2row() - Matrix indexing