scvelo - stochastic single cell RNA velocity
API¶
Import scVelo as:
import scvelo as scv
Read / Load¶
read(filename[, backed, sheet, ext, …]) |
Read file and return AnnData object. |
read_loom(filename[, sparse, cleanup, …]) |
Read .loom-formatted hdf5 file. |
Preprocessing (pp)¶
pp.filter_genes(data[, min_counts, …]) |
Filter genes based on number of cells or counts. |
pp.filter_genes_dispersion(data[, flavor, …]) |
Extract highly variable genes. |
pp.normalize_per_cell(data[, …]) |
Normalize each cell by total counts over all genes. |
pp.filter_and_normalize(data[, min_counts, …]) |
Filtering, normalization and log transform |
pp.moments(data[, n_neighbors, n_pcs, mode, …]) |
Computes moments for velocity estimation. |
Tools (tl)¶
tl.velocity(data[, vkey, mode, fit_offset, …]) |
Estimates velocities in a gene-specific manner |
tl.velocity_graph(data[, vkey, xkey, tkey, …]) |
Computes velocity graph based on cosine similarities. |
tl.velocity_embedding(data[, basis, vkey, …]) |
Computes the single cell velocities in the embedding |
tl.transition_matrix(adata[, vkey, basis, …]) |
Computes transition probabilities from velocity graph |
tl.terminal_states(data[, vkey, groupby, …]) |
Computes terminal states (root and end points). |
tl.rank_velocity_genes(data[, vkey, …]) |
Rank genes for velocity characterizing groups. |
tl.velocity_confidence(data[, vkey, copy]) |
Computes confidences of velocities. |
Plotting (pl)¶
pl.scatter([adata, x, y, basis, vkey, …]) |
Scatter plot along observations or variables axes. |
pl.velocity(adata[, var_names, basis, …]) |
Phase and velocity plot for set of genes. |
pl.velocity_graph(adata[, basis, vkey, …]) |
Plot of the velocity graph. |
pl.velocity_embedding(adata[, basis, vkey, …]) |
Scatter plot of velocities on the embedding. |
pl.velocity_embedding_grid(adata[, basis, …]) |
Scatter plot of velocities on a grid. |
pl.velocity_embedding_stream(adata[, basis, …]) |
Stream plot of velocities on the embedding. |
Datasets¶
datasets.toy_data(n_obs) |
Randomly samples from the Dentate Gyrus dataset. |
datasets.dentategyrus([adjusted]) |
Dentate Gyrus dataset from Hochgerner et al. |
datasets.forebrain() |
Developing human forebrain. |
Utils¶
utils.show_proportions(adata) |
Fraction of spliced/unspliced/ambiguous abundances |
utils.cleanup(data[, clean, keep, copy]) |
Deletes attributes not needed. |
utils.clean_obs_names(data[, base, …]) |
Cleans up the obs_names and identifies sample names. |
utils.merge(adata, ldata[, copy]) |
Merges two annotated data matrices. |
Settings¶
settings.set_figure_params([style, figsize, …]) |
Set resolution/size, styling and format of figures. |