If this tool published to cell, How the reviewer tested your tool? And they allowed you to publish this tool to cell with lots of problems?

When I am running this command: adata = dyn.sample_data.DentateGyrus() def dynamo_workflow(adata): adata = dyn.pp.recipe_monocle(adata)

dyn.tl.dynamics(adata)

dyn.tl.reduceDimension(adata)

dyn.tl.cell_velocities(adata, calc_rnd_vel=True)

dyn.vf.VectorField(adata, basis='umap')

dynamo_workflow(adata) I got this: |-----> recipe_monocle_keep_filtered_cells_key is None. Using default value from DynamoAdataConfig: recipe_monocle_keep_filtered_cells_key=True |-----> recipe_monocle_keep_filtered_genes_key is None. Using default value from DynamoAdataConfig: recipe_monocle_keep_filtered_genes_key=True |-----> recipe_monocle_keep_raw_layers_key is None. Using default value from DynamoAdataConfig: recipe_monocle_keep_raw_layers_key=True |-----> apply Monocole recipe to adata… |-----> <insert> pp to uns in AnnData Object. |-----------> <insert> has_splicing to uns[‘pp’] in AnnData Object. |-----------> <insert> has_labling to uns[‘pp’] in AnnData Object. |-----------> <insert> splicing_labeling to uns[‘pp’] in AnnData Object. |-----------> <insert> has_protein to uns[‘pp’] in AnnData Object. |-----> ensure all cell and variable names unique. |-----> ensure all data in different layers in csr sparse matrix format. |-----> ensure all labeling data properly collapased |-----------> <insert> tkey to uns[‘pp’] in AnnData Object. |-----------> <insert> experiment_type to uns[‘pp’] in AnnData Object. |-----? dynamo detects your data is size factor normalized and/or log transformed. If this is not right, plese set `normalized = False. |-----> filtering cells… |-----> <insert> pass_basic_filter to obs in AnnData Object. |-----> 18213 cells passed basic filters. |-----> filtering gene… |-----> <insert> pass_basic_filter to var in AnnData Object. |-----> 7960 genes passed basic filters. |-----> calculating size factor… |-----> selecting genes in layer: X, sort method: SVR… |-----> <insert> frac to var in AnnData Object. |-----> <insert> X_unspliced to layers in AnnData Object. |-----> <insert> X_spliced to layers in AnnData Object. |-----------> <insert> norm_method to uns[‘pp’] in AnnData Object. |-----> applying PCA … |-----> <insert> pca_fit to uns in AnnData Object. |-----> <insert> ntr to obs in AnnData Object. |-----> <insert> ntr to var in AnnData Object. |-----> cell cycle scoring… |-----> computing cell phase… |-----> [cell phase estimation] in progress: 100.0000% |-----> [cell phase estimation] finished [210.0349s] |-----> <insert> cell_cycle_phase to obs in AnnData Object. |-----> <insert> cell_cycle_scores to obsm in AnnData Object. |-----> [Cell Cycle Scores Estimation] in progress: 100.0000% |-----> [Cell Cycle Scores Estimation] finished [3.4422s] |-----> [recipe_monocle preprocess] in progress: 100.0000% |-----> [recipe_monocle preprocess] finished [16.9428s]

-----> dynamics_del_2nd_moments_key is None. Using default value from DynamoAdataConfig: dynamics_del_2nd_moments_key=False
AttributeError Traceback (most recent call last)
Input In [34], in <cell line: 1>()
----> 1 dynamo_workflow(adata)

Input In [30], in dynamo_workflow(adata) 1 def dynamo_workflow(adata): 2 adata = dyn.pp.recipe_monocle(adata) ----> 4 dyn.tl.dynamics(adata) 6 dyn.tl.reduceDimension(adata) 8 dyn.tl.cell_velocities(adata, calc_rnd_vel=True)

File /opt/anaconda3/lib/python3.9/site-packages/dynamo/tools/dynamics.py:297, in dynamics(adata, filter_gene_mode, use_smoothed, assumption_mRNA, assumption_protein, model, est_method, NTR_vel, group, protein_names, concat_data, log_unnormalized, one_shot_method, fraction_for_deg, re_smooth, sanity_check, del_2nd_moments, cores, tkey, **est_kwargs) 73 “”“Inclusive model of expression dynamics considers splicing, metabolic labeling and protein translation. It 74 support learning high-dimensional velocity vector samples for droplet based (10x, inDrop, drop-seq, etc), 75 scSLAM-seq, NASC-seq sci-fate, scNT-seq, scEU-seq, cite-seq or REAP-seq datasets. (…) 291 log_unnormalized: Whether to log transform unnormalized data. 292 “”” 294 del_2nd_moments = DynamoAdataConfig.use_default_var_if_none( 295 del_2nd_moments, DynamoAdataConfig.DYNAMICS_DEL_2ND_MOMENTS_KEY 296 ) –> 297 if “pp” not in adata.uns_keys(): 298 raise ValueError(f"\nPlease run dyn.pp.receipe_monocle(adata) before running this function!") 299 if tkey is None:

AttributeError: ‘NoneType’ object has no attribute ‘uns_keys’

[chansigit]

Dynamo is fantastic. @Spartanzhao is rude. good luck with your job interview @Xiaojieqiu

agree.

@Spartanzhao Zhao, Dynamo is not only a useful tool, but also a landscape perspective viewing the cells. Qiu and his team have been constantly improving the quality of this work. I believe It’s your loss if you miss this work for minor issues.

[hyjforesight]

Dynamo is fantastic. @Spartanzhao is rude. good luck with your job interview @Xiaojieqiu