Issue with dyn.tl.dynamics(adata)

[ergezhenshuai]

Hello dynamo， I ran into this problem when trying to run our dataset. What do you suggest? thank you very much. My code process is as follows,

import warnings warnings.filterwarnings('ignore') import dynamo as dyn dyn.dynamo_logger.main_silence()

adata = dyn.read_h5ad(r"E:\python\h5ad\a.h5ad") dyn.pp.recipe_monocle(adata) dyn.tl.dynamics(adata) dyn.vf.VectorField(adata, basis='umap') gene = "A2M" dyn.pd.perturbation(adata, gene, [-100], emb_basis="umap") dyn.pl.streamline_plot(adata, color=["cell_type", gene], basis="umap_perturbation")

The following problems occur， Since dyn.pl.phase_diagram in dynamo by default colors cells by its cell-cycle stage, you need to set color argument accordingly if confronting errors related to this. |-----> [recipe_monocle preprocess] in progress: 100.0000% |-----> [recipe_monocle preprocess] finished [3.4008s] |-----> calculating first/second moments... |-----> [moments calculation] in progress: 100.0000% |-----> [moments calculation] finished [9.6158s] Traceback (most recent call last): File "E:/python/test_dynamo_2.py", line 11, in dyn.tl.dynamics(adata) File "D:\anaconda\conda\envs\python\lib\site-packages\dynamo\tools\dynamics.py", line 413, in dynamics NTR_vel, File "D:\anaconda\conda\envs\python\lib\site-packages\dynamo\tools\utils.py", line 987, in get_data_for_kin_params_estimation subset_adata.layers["M_us"].T, File "D:\anaconda\conda\envs\python\lib\site-packages\anndata_core\aligned_mapping.py", line 113, in getitem _subset(self.parent_mapping[key], self.subset_idx), File "D:\anaconda\conda\envs\python\lib\site-packages\anndata_core\aligned_mapping.py", line 148, in getitem return self._data[key] KeyError: 'M_us'

[Xiaojieqiu]

thanks for this issue @ergezhenshuai . As I asked in the other thread, do you have spliced/unspliced layers for your adata object to start with? Dynamo will need to use these layers or the metabolic labeling data to perform velocity and vector field analyses for downstream predictions.

can you let me know what is the output after you type adata?

[ergezhenshuai]

Thank you for your answer, the output after we input adata。

AnnData object with n_obs × n_vars = 2280 × 26154 obs: 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'leiden_2.0' var: 'mt', 'n_cells_by_counts', 'mean_counts', 'log1p_mean_counts', 'pct_dropout_by_counts', 'total_counts', 'log1p_total_counts', 'n_cells', 'mean', 'std' uns: 'leiden', 'leiden_2.0_colors', 'neighbors', 'pca', 'spatial_neighbors', 'umap' obsm: 'X_pca', 'X_umap', 'spatial' varm: 'PCs' obsp: 'connectivities', 'distances', 'spatial_connectivities', 'spatial_distances'

Output after using dyn.pp.recipe_monocle(adata)，

AnnData object with n_obs × n_vars = 2280 × 26154 obs: 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'leiden_2.0', 'nGenes', 'nCounts', 'pass_basic_filter', 'Size_Factor', 'initial_cell_size' var: 'mt', 'n_cells_by_counts', 'mean_counts', 'log1p_mean_counts', 'pct_dropout_by_counts', 'total_counts', 'log1p_total_counts', 'n_cells', 'mean', 'std', 'nCells', 'nCounts', 'pass_basic_filter', 'log_cv', 'log_m', 'score', 'frac', 'use_for_pca' uns: 'leiden', 'leiden_2.0_colors', 'neighbors', 'pca', 'spatial_neighbors', 'umap', 'pp', 'velocyto_SVR', 'PCs', 'explained_variance_ratio_', 'pca_mean', 'pca_fit', 'feature_selection', 'cell_phase_genes' obsm: 'X_pca', 'X_umap', 'spatial', 'X' varm: 'PCs' obsp: 'connectivities', 'distances', 'spatial_connectivities', 'spatial_distances'

[Xiaojieqiu]

as I said, your data doesn't have spliced . and unspliced layers and only has total RNA info. you will need to first get these layers to start with. You may consider using kb-python: https://github.com/pachterlab/kb_python

[ergezhenshuai]

Thanks for your suggestion, we processed our data to have spliced and unspliced layers. But when we used dyn.tl.cell_velocities(adata), the following error occurred: Traceback (most recent call last): File "E:/python/test_dynamo_2.py", line 17, in dyn.tl.cell_velocities(adata) File "D:\anaconda\conda\envs\python\lib\site-packages\dynamo\tools\cell_velocities.py", line 253, in cell_velocities min_delta=min_delta, File "D:\anaconda\conda\envs\python\lib\site-packages\dynamo\tools\utils.py", line 1801, in set_transition_genes reserve_minimal_genes_by_gamma_r2(adata, store_key, minimal_gene_num=minimal_gene_num) File "D:\anaconda\conda\envs\python\lib\site-packages\dynamo\tools\utils.py", line 268, in reserve_minimal_genes_by_gamma_r2 raise ValueError("adata.var.%s does not have enough values that are not NA." % (var_store_key)) ValueError: adata.var.use_for_transition does not have enough values that are not NA.

We found that in the adata output, var does not have use_for_transition and obsm does not have velocity_pca，velocity_umap, etc.In this case, how should we handle it?

[Xiaojieqiu]

please pass transition_genes = adata.var_names[adata.var.use_for_pca] to the dyn.tl.cell_velocities function

[ergezhenshuai]

Thank you for your answer, I have a problem, when the image is saved and displayed, the image is not the same

dyn.pd.perturbation(adata, gene, [-100], emb_basis="umap") dyn.pl.streamline_plot(adata, color=["cell_type", gene], basis="umap_perturbation", save_show_or_return="save", save_kwargs={"path": "E:\python\plot\", "prefix": 'scatter', "dpi": None, "ext": 'svg', "transparent": True, "close": True, "verbose": True})

Below is when the image is showed,

Below is when the image is saved, Total RNA stream line plot don't have arrows and it is missing a plot.

[ergezhenshuai]

Thanks for your answer, dynamo is a very useful tool.