Analysis

SingleCell.qc_metrics	Adds quality-control metrics to obs for each cell: the sum of counts across all genes (num_counts), the number of genes with non-zero expression (num_genes), and the fraction of counts that are mitochondrial (mito_fraction).
SingleCell.qc	Adds a Boolean column to obs indicating which cells passed quality control (QC), or subsets to these cells if subset=True.
SingleCell.find_doublets	Find doublets using cxds (co-expression-based doublet scoring).
SingleCell.get_sample_covariates	Get a DataFrame of sample-level covariates, i.e. the columns of obs that are the same for all cells within each sample.
SingleCell.pseudobulk	Pseudobulk a SingleCell dataset with sample ID and cell type columns.
SingleCell.hvg	Select highly variable genes using the same approach as Seurat.
SingleCell.normalize	Normalize this SingleCell dataset's counts.
SingleCell.pca	Compute principal components (PCs) across cells.
SingleCell.neighbors	Calculate the num_neighbors nearest neighbors of each cell.
SingleCell.shared_neighbors	Calculate the shared nearest neighbor graph of this dataset's cells.
SingleCell.harmonize	Harmonize this SingleCell dataset with other datasets, or harmonize multiple batches of the same dataset, with Harmony2.
SingleCell.cluster	Cluster cells into cell types using Leiden clustering.
SingleCell.label_transfer_from	Transfer cell-type labels from another dataset to this one, using the two datasets' Harmony embeddings from harmonize().
SingleCell.umap	Calculate a two-dimensional embedding of this SingleCell dataset with UMAP (Uniform Manifold Approximation and Projection), suitable for plotting with plot_embedding().
SingleCell.pacmap	Calculate a two-dimensional embedding of this SingleCell dataset suitable for plotting with plot_embedding().
SingleCell.localmap	Calculate a two-dimensional embedding of this SingleCell dataset suitable for plotting with plot_embedding().
SingleCell.find_markers	Find "marker genes" that distinguish each cell type from all other cell types.
SingleCell.plot_heatmap	Plot a heatmap of the count of each combination of two categorical columns, x and y.
SingleCell.plot_markers	Make a dot plot of a set of marker genes of interest across cell types.
SingleCell.plot_umap	Plot a UMAP embedding created with umap().
SingleCell.plot_pacmap	Plot a PaCMAP embedding created with pacmap().
SingleCell.plot_localmap	Plot a LocalMAP embedding created with localmap().
SingleCell.plot_embedding	Plot the specified 2D embedding.