Conos                   Conos R6 class
basicSeuratProc         Create and preprocess a Seurat object
bestClusterThresholds   Find threshold of cluster detectability
bestClusterTreeThresholds
                        Find threshold of cluster detectability in
                        trees of clusters
buildWijMatrix          Rescale the weights in an edge matrix to match
                        a given perplexity.
convertToPagoda2        Convert Conos object to Pagoda2 object
edgeMat<-               Set edge matrix edgeMat with certain values on
                        sample
estimateWeightEntropyPerCell
                        Estimate entropy of edge weights per cell
                        according to the specified factor. Can be used
                        to visualize alignment quality according to
                        this factor.
findSubcommunities      Increase resolution for a specific set of
                        clusters
getBetweenCellTypeCorrectedDE
                        Compare two cell types across the entire panel
getBetweenCellTypeDE    Compare two cell types across the entire panel
getCellNames            Access cell names from sample
getClustering           Access clustering from sample
getCountMatrix          Access count matrix from sample
getEmbedding            Access embedding from sample
getGeneExpression       Access gene expression from sample
getGenes                Access genes from sample
getOverdispersedGenes   Access overdispersed genes from sample
getPca                  Access PCA from sample
getPerCellTypeDE        Do differential expression for each cell type
                        in a conos object between the specified subsets
                        of apps
getRawCountMatrix       Access raw count matrix from sample
getSampleNamePerCell    Retrieve sample names per cell
greedyModularityCut     Performs a greedy top-down selective cut to
                        optmize modularity
p2app4conos             Utility function to generate a pagoda2 app from
                        a conos object
plotClusterBarplots     Plots barplots per sample of composition of
                        each pagoda2 application based on selected
                        clustering
plotClusterBoxPlotsByAppType
                        Generate boxplot per cluster of the proportion
                        of cells in each celltype
plotComponentVariance   Plot fraction of variance explained by the
                        successive reduced space components (PCA, CPCA)
plotDEheatmap           Plot a heatmap of differential genes
projectKNNs             Project a distance matrix into a
                        lower-dimensional space.
rawMatricesWithCommonGenes
                        Get raw matrices with common genes
saveConosForScanPy      Save Conos object on disk to read it from
                        ScanPy
saveDEasCSV             Save differential expression as table in *csv
                        format
saveDEasJSON            Save differential expression results as JSON
scanKModularity         Scan joint graph modularity for a range of k
                        (or k.self) values Builds graph with different
                        values of k (or k.self if scan.k.self=TRUE),
                        evaluating modularity of the resulting
                        multilevel clustering NOTE: will run
                        evaluations in parallel using con$n.cores
                        (temporarily setting con$n.cores to 1 in the
                        process)
sgdBatches              Calculate the default number of batches for a
                        given number of vertices and edges. The formula
                        used is the one used by the 'largeVis'
                        reference implementation.  This is
                        substantially less than the recommendation E *
                        10000 in the original paper.
small_panel.preprocessed
                        Small pre-processed data from Pagoda2, two
                        samples, each dimension (1000, 100)
stableTreeClusters      Determine number of detectable clusters given a
                        reference walktrap and a bunch of permuted
                        walktraps
