Function reference
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ComputeSNNasym() - Calculates SNN from adjacency matrix with uneven number of neighbours per row.
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NormLaplacian() - Calculate Normalized Graph Laplacian
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aR_metric() - calculates association ratio between to columns in a matrix.
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add_caclust_sce() - Add caclust object to SingleCellExperiment object
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add_zero_dim() - Add an extra 0 dimension to vector
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annotate_biclustering() - Perform gene overrepresentation analysis and annotate biclusters.
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annotate_by_goa() - Annotate CAbiNet results by gene overrepresentation analysis results.
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as.caclust() - Try converting to caclust object from list or biclustlib.
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assign_clusters_GMM() - Assign cluster to cells/genes
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assign_cts() - Assign cell types to clusters using the Hungarian algorithm.
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augment_vector() - Transforms vectors such that the max. inner product (MIP) search is equal to a NN search with euclidean distances.
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biMAP() - Compute biMAP
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biMAP_plotter() - biMAP plotter
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bicplot() - Plot of 2D CA projection of the clustering results.
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ca_biMAP() - Compute biMAP basedon CA results
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caclust-class - An S4 class that contains all elements needed for CA.
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caclust() - caclust
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calc_assR() - Calculate Association Ratio
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calc_distances() - Calculate distances for bigraph
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calc_euclidean() - Calculate euclidean distance
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calc_overlap() - WIP replacement for `determine_overlap` function
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calc_overlap_deprecated() - Deprecated, slower old version of calc_overlap. Only included for testing.
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cell_clusters() - Get cell clusters
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cellmarker_v2 - CellMarker V2
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check_caclust() - Checks if caclust-class was constructed correctly
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check_caobj_sce() - check_caobj_sce
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contour_plot() - internal helper to plot contour biMAP
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convert_to_biclust() - Converts CAclust results to biclustlib results
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create_bigraph() - Combine kNN graphs to large cell-gene adjecency matrix
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determine_overlap() - Determines the overlap of chosen genes between nearest neighbour cells. It works faster on sparse matrix than on dense matrix.
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eigengap() - Detecting eigengap.
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feature_biMAP() - plot biMAP with gene expression
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filter_gene_sets() - Filter gene sets by size
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format_gene_sets() - Changes long format gene set data frame into a named list of gene sets.
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gene_clusters() - Get gene clusters
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get_bimap() - Get biMAP coordinates
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get_caclust() - Get caclust object from SingleCellExperiment object.
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get_cell_prob() - Get probablities of cell clusters
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get_eigen() - Get eigenvectors from spectral clustering
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get_gene_prob() - Get probablities of gene clusters
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get_majority() - Determines majority in a vector
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get_ncells() - Get the number of cells from each cluster per hexbin
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get_params() - Get parameters for generating clustering
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get_snn() - Get SNN graph
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hex_plot() - internal helper to plot hex biMAP
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indx_to_spmat() - Convert index matrix to sparse matrix.
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is.empty() - Helper function to check if object is empty.
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load_gene_set() - Load the required gene set.
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make_SNN() - Create SNN-graph from caobj
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metadata_biMAP() - Plot continous or categorical data as a biMAP
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mix() - Shuffle rows of a data frame for better plotting.
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mix_rgb() - Mixes the colors of two clusters proportionally.
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new_caclust() - Create new caclust object
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optimal_km() - An integration of several runs of kmens with different random seeds
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optimal_skm() - An integration of several runs of skmens with different random seeds
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parse_ratio() - turns string of a ratio in a number.
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per_cluster_goa() - Perform gene set overrepresentation analysis for each bicluster and annotate cells based on the best match.
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perform_goa() - Adapted from `DOSE:::enricher_interal`. Performs Gene Overrepresentation Analysis.
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plot_contour_biMAP() - Plot contour biMAP
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plot_feature_biMAP() - BiMAP visualization of feature expression.
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plot_goa_res() - Plot gene overrepresentation analysis results.
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plot_hex_biMAP() - Plot biMAP with hexagonal bins
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plot_metadata_biMAP() - Plot continous or categorical data as a biMAP
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plot_scatter_biMAP()plot_biMAP() - Plots a biMAP scatter plot
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rm_monoclusters() - Remove clusters only consisting of cells/genes
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run_biMAP() - Run UMAP embedding for cell-gene graph built up by caclust.
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run_caclust() - Run biclustering
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run_leiden() - Leiden clustering on bigraph
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run_spectral() - Run spectral clustering
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scatter_plot() - internal helper to plot scatter biMAP
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show.caclust()show(<caclust>) - Print caclust object in console
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tbl_paste() - concatenate table() results for hex_plot.