Dyngen data preparation

Contents

Dyngen data preparation#

This notebook prepares the dyngen-generated datasets for velocity, latent time, and GRN inference. Here, we only demonstrate how preprocessing was performed and how all algorithms were applied on the scale-1 datasets. For datasets of other scales, the analyses are carried out in exactly the same way.

Library imports#

from tqdm import tqdm

import numpy as np
import pandas as pd
from numpy.typing import ArrayLike

import anndata as ad
import scanpy as sc
import scvelo as scv
from anndata import AnnData
from velovi import preprocess_data

from rgv_tools import DATA_DIR

General settings#

scv.settings.verbosity = 3

Function definitions#

def define_uns_elems(adata: AnnData) -> None:
    """Define prior regulation graph."""
    grn = np.zeros([adata.n_vars, adata.n_vars])
    df = adata.uns["regulatory_network"][["regulator", "target", "effect"]].copy()  # extracts regulatory network data

    df = pd.pivot(df, index="regulator", columns="target", values="effect").fillna(
        0
    )  # rows as regulators, columns as targets
    df[df != 0] = 1
    grn[np.ix_(adata.var_names.get_indexer(df.index), adata.var_names.get_indexer(df.columns))] = df.values

    adata.uns["skeleton"] = grn
    adata.uns["regulators"] = adata.var_names
    adata.uns["targets"] = adata.var_names
    adata.uns["network"] = grn

def update_data(adata: AnnData) -> None:
    """Update dyngen-simulated data to include only relevant information in the standard format."""
    adata.X = adata.layers["counts_spliced"]

    adata.layers["unspliced"] = adata.layers.pop("counts_unspliced")
    adata.layers["spliced"] = adata.layers.pop("counts_spliced")
    adata.layers["true_velocity"] = adata.layers.pop("rna_velocity")
    adata.layers["true_velocity"] = adata.layers["true_velocity"].toarray()
    adata.layers["unspliced_raw"] = adata.layers["unspliced"].copy()
    adata.layers["spliced_raw"] = adata.layers["spliced"].copy()

    del adata.layers["counts_protein"]
    del adata.layers["logcounts"]

    adata.obs.rename(columns={"sim_time": "true_time"}, inplace=True)  # preserving simulated time as ground truth
    adata.obs.drop(columns=["step_ix", "simulation_i"], inplace=True)

    adata.var.rename(
        columns={"transcription_rate": "true_alpha", "splicing_rate": "true_beta", "mrna_decay_rate": "true_gamma"},
        inplace=True,
    )
    columns_to_keep = ["true_alpha", "true_beta", "true_gamma", "is_tf"]
    adata.var.drop(columns=adata.var.columns.difference(columns_to_keep), inplace=True)

    slots = list(adata.uns.keys())
    for slot in slots:
        if slot in ["network", "regulatory_network", "skeleton", "regulators", "targets"]:
            adata.uns[f"true_{slot}"] = adata.uns.pop(slot)
        else:
            del adata.uns[slot]

    adata.obsm["true_sc_network"] = adata.obsm.pop("regulatory_network_sc")
    del adata.obsm["dimred"]

    adata.obs_names = adata.obs_names.str.replace("cell", "cell_")

def get_sc_grn(adata: AnnData) -> ArrayLike:
    """Compute cell-specific GRNs."""
    true_sc_grn = []

    for cell_id in range(adata.n_obs):
        grn = np.zeros([adata.n_vars, adata.n_vars])
        df = adata.uns["true_regulatory_network"][["regulator", "target"]].copy()
        df["value"] = adata.obsm["true_sc_network"][cell_id, :].toarray().squeeze()

        df = pd.pivot(df, index="regulator", columns="target", values="value").fillna(0)
        grn[np.ix_(adata.var_names.get_indexer(df.index), adata.var_names.get_indexer(df.columns))] = df.values
        true_sc_grn.append(grn)
    return np.dstack(true_sc_grn)

Constants#

DATASET = "dyngen"

COMPLEXITY = "complexity_1"

SAVE_DATA = True
if SAVE_DATA:
    (DATA_DIR / DATASET / COMPLEXITY / "processed").mkdir(parents=True, exist_ok=True)

Data loading#

cnt = 0
for filename in tqdm((DATA_DIR / DATASET / COMPLEXITY / "raw").iterdir()):
    if filename.suffix != ".h5ad":
        continue

    simulation_id = int(filename.stem.removeprefix("dataset_sim"))
    print(f"Run {cnt}, dataset {simulation_id}.")
    adata = ad.io.read_h5ad(filename)

    define_uns_elems(adata=adata)
    update_data(adata=adata)
    adata.uns["true_sc_grn"] = get_sc_grn(adata=adata)

    scv.pp.filter_and_normalize(adata, min_shared_counts=10, log=False)
    sc.pp.log1p(adata)
    sc.tl.pca(adata)
    sc.pp.neighbors(adata, n_neighbors=30, n_pcs=30)
    scv.pp.moments(adata)

    adata = preprocess_data(adata, filter_on_r2=True)

    mask = pd.Index(adata.uns["true_regulators"]).isin(adata.var_names)
    for uns_key in ["network", "skeleton", "sc_grn"]:
        adata.uns[f"true_{uns_key}"] = adata.uns[f"true_{uns_key}"][np.ix_(mask, mask)]

    for key in adata.uns:
        if isinstance(adata.uns[key], pd.Index):
            adata.uns[key] = list(adata.uns[key])  # Convert to list

    adata.write_zarr(DATA_DIR / DATASET / COMPLEXITY / "processed" / f"simulation_{simulation_id}.zarr")
    cnt += 1

0it [00:00, ?it/s]

Run 0, dataset 10.
Filtered out 86 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.

2025-04-28 21:23:33.257567: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
E0000 00:00:1745868214.003834 3902758 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
E0000 00:00:1745868214.428478 3902758 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
W0000 00:00:1745868215.969445 3902758 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1745868215.969489 3902758 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1745868215.969493 3902758 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
W0000 00:00:1745868215.969497 3902758 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.

computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
1it [02:06, 126.49s/it]

Run 1, dataset 1.
Filtered out 139 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
2it [02:23, 62.08s/it] 

Run 2, dataset 6.
Filtered out 119 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
3it [02:44, 43.26s/it]

Run 3, dataset 28.
Filtered out 66 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
4it [03:04, 34.02s/it]

Run 4, dataset 21.
Filtered out 148 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
5it [03:21, 28.01s/it]

Run 5, dataset 8.
Filtered out 111 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
6it [03:38, 24.39s/it]

Run 6, dataset 9.
Filtered out 171 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
7it [03:55, 21.85s/it]

Run 7, dataset 25.
Filtered out 91 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
8it [04:15, 21.39s/it]

Run 8, dataset 17.
Filtered out 104 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
9it [04:41, 22.64s/it]

Run 9, dataset 12.
Filtered out 85 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
11it [04:58, 16.07s/it]

Run 10, dataset 30.
Filtered out 158 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
12it [05:16, 16.58s/it]

Run 11, dataset 4.
Filtered out 124 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
13it [05:34, 16.89s/it]

Run 12, dataset 14.
Filtered out 16 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
14it [05:53, 17.56s/it]

Run 13, dataset 5.
Filtered out 230 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
15it [06:09, 17.13s/it]

Run 14, dataset 18.
Filtered out 136 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
16it [06:26, 16.97s/it]

Run 15, dataset 16.
Filtered out 171 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
17it [06:45, 17.59s/it]

Run 16, dataset 27.
Filtered out 105 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
18it [07:02, 17.23s/it]

Run 17, dataset 29.
Filtered out 187 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
19it [07:18, 16.94s/it]

Run 18, dataset 3.
Filtered out 338 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
20it [07:33, 16.42s/it]

Run 19, dataset 20.
Filtered out 132 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
21it [07:48, 15.97s/it]

Run 20, dataset 7.
Filtered out 107 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
22it [08:04, 16.11s/it]

Run 21, dataset 2.
Filtered out 103 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
23it [08:22, 16.72s/it]

Run 22, dataset 24.
Filtered out 165 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
24it [08:42, 17.49s/it]

Run 23, dataset 26.
Filtered out 48 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
25it [08:59, 17.34s/it]

Run 24, dataset 15.
Filtered out 187 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
27it [09:15, 13.11s/it]

Run 25, dataset 23.
Filtered out 130 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
28it [09:31, 13.70s/it]

Run 26, dataset 11.
Filtered out 201 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
29it [09:46, 14.26s/it]

Run 27, dataset 19.
Filtered out 177 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
30it [10:01, 14.45s/it]

Run 28, dataset 13.
Filtered out 47 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
31it [10:18, 15.12s/it]

Run 29, dataset 22.
Filtered out 117 genes that are detected 10 counts (shared).
Normalized count data: X, spliced, unspliced.
computing moments based on connectivities
    finished (0:00:00) --> added 
    'Ms' and 'Mu', moments of un/spliced abundances (adata.layers)
computing velocities
    finished (0:00:00) --> added 
    'velocity', velocity vectors for each individual cell (adata.layers)

/home/icb/yifan.chen/miniconda3/envs/regvelo-py310/lib/python3.10/site-packages/pandas/core/algorithms.py:522: DeprecationWarning: np.find_common_type is deprecated.  Please use `np.result_type` or `np.promote_types`.
See https://numpy.org/devdocs/release/1.25.0-notes.html and the docs for more information.  (Deprecated NumPy 1.25)
  common = np.find_common_type([values.dtype, comps_array.dtype], [])
33it [10:34, 19.23s/it]