# Clustering on Network of Samples

## Documentation for package ‘conos’ version 1.4.0

- DESCRIPTION file.

## Help Pages

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.
buildWijMatrix.CsparseMatrix | Rescale the weights in an edge matrix to match a given perplexity.
buildWijMatrix.TsparseMatrix | Rescale the weights in an edge matrix to match a given perplexity.
collapseCellsByType | Collapse count matrices by cell type, given min/max number of cells
Conos | Conos R6 class
convertToPagoda2 | Convert Conos object to Pagoda2 object
edgeMat | Set edge matrix edgeMat with certain values on sample
edgeMat-method | Set edge matrix edgeMat with certain values on sample
edgeMat<- | Set edge matrix edgeMat with certain values on sample
edgeMat<--method | 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
getCellNames-method | Access cell names from sample
getClustering | Access clustering from sample
getClustering-method | Access clustering from sample
getCountMatrix | Access count matrix from sample
getCountMatrix-method | Access count matrix from sample
getEmbedding | Access embedding from sample
getEmbedding-method | Access embedding from sample
getGeneExpression | Access gene expression from sample
getGeneExpression-method | Access gene expression from sample
getGenes | Access genes from sample
getGenes-method | Access genes from sample
getOverdispersedGenes | Access overdispersed genes from sample
getOverdispersedGenes-method | Access overdispersed genes from sample
getPca | Access PCA from sample
getPca-method | 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
getRawCountMatrix-method | 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