problem running Scribe(adata, t0_key='spliced', t1_key='unspliced')

[polakme]

Hi Xiaojie,
A really cool tool for building the network, thanks for putting it together.
When running NASC_seq_Jurkat_T_cell_demo.ipynb with the demo data I was not able to calculate causality score running Scribe(adata, t0_key='spliced', t1_key='unspliced').

Full error text:

IndexError Traceback (most recent call last)
in
----> 1 Scribe(adata, t0_key='spliced', t1_key='unspliced')

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/Scribe/Scribe.py in causal_net_dynamics_coupling(adata, TFs, Targets, guide_keys, t0_key, t1_key, normalize, drop_zero_cells, copy)
127 z_orig = [[i] for i in z_orig]
128
--> 129 causal_net.loc[g_a, g_b] = cmi(x_orig, y_orig, z_orig)
130
131 adata.uns['causal_net'] = {"RDI": causal_net.fillna(0)}

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/Scribe/information_estimators.py in cmi(x_orig, y_orig, z_orig, normalization, k)
144 N = len(x)
145
--> 146 dx = len(x[0])
147 dy = len(y[0])
148 dz = len(z[0])

IndexError: list index out of range

Fixed with your advise by setting
drop_zero_cells=False in the function causal_net_dynamics_coupling

Scribe(adata, t0_key='spliced', t1_key='unspliced', drop_zero_cells=False)

Hope this report maybe useful for others
Thanks!

[limenglingll]

Hi Xiaojie,
A really cool tool for building the network, thanks for putting it together.
When running NASC_seq_Jurkat_T_cell_demo.ipynb with the demo data I was not able to calculate causality score running Scribe(adata, t0_key='spliced', t1_key='unspliced').

Calculate causality score (RDI) from each TF to potential target:: 0%| | 0/25 [00:00<?, ?it/s]
Why?