Clustering on Network of Samples
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘conos’ version 1.5.2
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. |
| 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 |
| velocityInfoConos | RNA velocity analysis on samples integrated with conos Create a list of objects to pass into gene.relative.velocity.estimates function from the velocyto.R package |