Zehua Zeng

> Hi, You can use `adata.obs['pt']=v0.single_cell_pt_markov` to extract the pseudotime calculated by VIA.

Hi, You can use this code to solve: ```python type(v0)#via_object of pyVIA cluster_i_loc=np.where(np.asarray(v0.labels) == 1)[0] dict(adata.obs.iloc[cluster_i_loc].value_counts('label')) ``` `cluster_i_loc` give the position of the composition of pie chart you interested in...

Hi @wangjiawen2013 I recently encountered the same issue with pyVIA's visual beautification. You can use the raw color to plot celltype with VIA in Pyomic. The tutorial of pyVIA can...

Hi, You can set the following code before `survial_analysis` ```python from scipy import sparse LIHC_tcga.adata.layers['deseq_normalize']=sparse.csr_matrix(LIHC_tcga.adata.layers['deseq_normalize']) ```

We have fixed this error in the version of `1.6.4`.

Hi, you can try install by: ``` conda create -n omicverse python=3.10 conda activate omicverse conda install mamba -c conda-forge mamba install jax jaxlib -c conda-forge pip3 install torch torchvision...

Hi, You need to set the obs_names of adata unique before quantity control.

Thanks for the suggestion, the latest version of the tutorial has added some modified definitions. However, I still feel that the latest tutorial raises questions.

Hi, Thanks for your support, the same issue could be found in #70

Hi @RubyLiu206 , I don't quite understand why you chose 2,000 highly variable genes for deconvolution, my tutorial uses raw counts and uses all genes(https://omicverse.readthedocs.io/en/latest/Tutorials-bulk2single/t_bulk2single/), you can scale down the...