phylovelo.pseudo_time
Functions
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Get nearest neighbors of the target |
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Given two points' coordinate and velocity, calculate the time interval |
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Build graph to construct MST |
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Prim algorithm to build MST from graph |
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Calculate the phyloVelo pseudotime |
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Calculate pseudotime directly from robustly oriented MEG expression. |
Module Contents
- get_nearest_neighbor(data: numpy.ndarray, target: int, n_neighbors: int = 10)
Get nearest neighbors of the target
- Args:
- data:
Data to train knn
- target:
Target point to get nearest neighbors
- n_neighbors:
How many nearest neighbors to return
- Returns:
- list:
Euclidean distance from target to neighbors
- list:
Neighbors’ indices
- _as_float_array(x)
- _normalize_01(x, robust_quantiles=None)
- _normalize_with_bounds(x, lo, hi)
- _time_intervals(pt1, pt2, v1, v2)
- time_interval(pt1: numpy.ndarry, pt2: numpy.ndarry, v1: numpy.ndarry, v2: numpy.ndarry)
Given two points’ coordinate and velocity, calculate the time interval
- Args:
- pt1:
Coordinate of one point
- pt2:
Coordinate of the other point
- v1:
Velocity of one point
- v2:
Velocity of the other point
- Return:
- float:
Time interval
- _build_knn_adjacency(pts, v, n_neighbors=30)
- _connected_components(adjacency)
- _bridge_components(adjacency, pts, v, root=0)
- _prim_edges(adjacency, root=0)
- _graph_pseudotime(pts, v, n_neighbors=30, root=0, robust_quantiles=(0.01, 0.99))
- graph_dict(pts: numpy.ndarry, v: numpy.ndarry, n_neighbors: int = 30)
Build graph to construct MST
- Args:
- pts:
All cells’ coordinate in embedding
- v:
Phylo velocity
- n_neighbors:
N nearest neighbors to build MST
- Return:
- dict:
Graph to build MSt
- prim(graph, root)
Prim algorithm to build MST from graph
- _sample_cells(index, r_sample, random_state=None)
- _positions_for_names(index, names)
- _get_expression_data(obj, target)
- _meg_pseudotime_scores(X, lo, spread, signs, weights, aggregation)
- calc_phylo_pseudotime(sd: scData, n_neighbors: int = 30, r_sample: float = 1, method: str = 'graph', target: str = 'x_normed', random_state: int = None)
Calculate the phyloVelo pseudotime
- Args:
- sd:
sc data
- n_neighbors:
N nearest neighbors to build MST. The smaller the number, the faster the calculation, but there is a chance of error
- r_sample:
[0-1], random sample a subset calculate pseudotime.
- method:
‘graph’ uses embedding velocities and a kNN MST; ‘meg’ uses robust MEG expression.
- target:
Expression matrix used when method=’meg’.
- random_state:
Seed for subsampling.
- Return:
scData.phylo_pseudotime
- calc_meg_pseudotime(sd: scData, target: str = 'x_normed', genes: list = None, robust_quantiles: tuple = (0.05, 0.95), aggregation: str = 'median', min_genes: int = 3, query_data=None, query_sd: scData = None, query_target: str = None)
Calculate pseudotime directly from robustly oriented MEG expression.
- Args:
- sd:
sc data
- target:
Expression matrix to use, usually ‘x_normed’ or ‘count’.
- genes:
MEGs to use. Default uses sd.megs.
- robust_quantiles:
Lower and upper quantiles used to clip per-gene expression.
- aggregation:
‘median’ for robust L1 aggregation or ‘weighted_mean’.
- min_genes:
Minimum number of usable MEGs.
- query_data:
Independent expression matrix (cells x genes) to score with the reference dataset’s MEGs, velocity directions, and robust scaling.
- query_sd:
Independent scData object. Uses query_target or target as expression matrix and writes query pseudotime to query_sd.phylo_pseudotime.
- query_target:
Expression matrix name for query_sd. Default: same as target.
- Return:
sd if no query is provided; query pseudotime array if query_data is provided; query_sd if query_sd is provided.