KeyError with running dynamics

[michelle-mantilla]

Hello, I am very new to using this package and I am unable to run the dynamics function on my data because of a KeyError. I am not sure how to address this issue, I have pasted the error message below. Thanks!

File ~/Library/Python/3.10/lib/python/site-packages/dynamo/tools/dynamics.py:404, 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)
    389     if model.lower() == "stochastic" or use_smoothed:
    390         moments(subset_adata)
    391 (
    392     U,
    393     Ul,
    394     S,
    395     Sl,
    396     P,
    397     US,
    398     U2,
    399     S2,
    400     t,
    401     normalized,
    402     ind_for_proteins,
    403     assump_mRNA,
--> 404 ) = get_data_for_kin_params_estimation(
    405     subset_adata,
    406     has_splicing,
    407     has_labeling,
...
File /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/anndata/_core/aligned_mapping.py:148, in AlignedActualMixin.__getitem__(self, key)
    147 def __getitem__(self, key: str) -> V:
--> 148     return self._data[key]

KeyError: 'M_us'

[Xiaojieqiu]

Thanks @michelle-mantilla

This means that the M_us is not calculated. What is your input adata? Do you have spliced / unspliced layers or new and total RNA layers?

Thanks

[michelle-mantilla]

Hello @Xiaojieqiu !

My input data is scRNA seq and TCR of CD4 cells. When I run the monocle recipe on my data, it returns back that no layers exist in my adata.

Thank you

[Xiaojieqiu]

Please consider generate unspliced/spliced RNA layers for your data using kb-python before running dynamo: https://github.com/pachterlab/kb_python

dynamo assumes you have such information --- otherwise it doesn't make sense for RNA velocity vector field analyses. we will also provide a new method that generates to datasets without splicing info etc. soon. Please check back in a few weeks.

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