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jaydu1 / VITAE

Joint Trajectory Inference for Single-cell Genomics Using Deep Learning with a Mixture Prior
https://jaydu1.github.io/VITAE/
MIT License
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error in model.preprocess_data if an annData object is given as input in model.get_data #1

Closed rmathieu25 closed 3 years ago

rmathieu25 commented 3 years ago

Hello,

Thanks for developing VITAE.

I tried to use VITAE but I have an issue regarding the model.preprocess_data when I give an annData object as an input of model.get_data function.

The preprocession should be done by scanpy which it is installed but I get the error: 

# fit in data
model.get_data(adata=data,                   # count or expression matrix, (dense or sparse) numpy array 
               labels = data.obs['cluster_label'],       # (optional) labels, which will be converted to string
               gene_names = data.var['features'], # (optional) gene names, which will be converted to string
               cell_names = data.obs['sample_name']    # (optional) cell names, which will be converted to string
              )

# preprocess data
model.preprocess_data(gene_num = 2000,        # (optional) maximum number of influential genes to keep (the default is 2000)
                      data_type = 'UMI', # (optional) data_type can be 'UMI', 'non-UMI' or 'Gaussian' (the default is 'UMI')
                      npc = 64              # (optional) number of PCs to keep if data_type='Gaussian' (the default is 64)#)
                      )
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-7-aa66b286b1ac> in <module>()
     35 model.preprocess_data(gene_num = 2000,        # (optional) maximum number of influential genes to keep (the default is 2000)
     36                       data_type = 'UMI', # (optional) data_type can be 'UMI', 'non-UMI' or 'Gaussian' (the default is 'UMI')
---> 37                       npc = 64              # (optional) number of PCs to keep if data_type='Gaussian' (the default is 64)#)
     38                       )

2 frames
/usr/local/lib/python3.7/dist-packages/VITAE/preprocess.py in _recipe_seurat(adata, gene_num)
    238     This uses a particular preprocessing
    239     """
--> 240     cell_mask = sc.pp.filter_cells(adata, min_genes=200, inplace=False)[0]
    241     adata = adata[cell_mask,:]
    242     gene_mask = sc.pp.filter_genes(adata, min_cells=3, inplace=False)[0]

NameError: name 'sc' is not defined

I do not understand what is the issue because you import scanpy as sc in your defined function?

Thank you in advance.

Best regards.

jaydu1 commented 3 years ago

Hi,

Thanks for reporting the issue. The problem has been fixed in the latest version v1.1.5.

Another workaround is to first preprocess your data with scanpy on your own and then pass the preprocessed anndata object to VITAE functions. This allows you to have more flexibility to preprocess the data.

Best.

rmathieu25 commented 3 years ago

Hello,

Thank you for you answer.

How can I install the last version of VITAE? I cannot install with the git+[url] option because you have not a setup file, right?

I tried to use the command line:

!pip install --upgrade --force-reinstall pyvitae

but still the version 1.1.4 is installed.

Actually, I tried to prepoccess the adata object beforehand but I am having the following issues:

# fit in data
model.get_data(adata=data,                   # count or expression matrix, (dense or sparse) numpy array 
               labels = data.obs['cluster_label'],       # (optional) labels, which will be converted to string
               gene_names = data.var['features'], # (optional) gene names, which will be converted to string
               cell_names = data.obs['sample_name']    # (optional) cell names, which will be converted to string
              )

# preprocess data
model.preprocess_data(gene_num = 2000,        # (optional) maximum number of influential genes to keep (the default is 2000)
                     data_type = 'Gaussian', # (optional) data_type can be 'UMI', 'non-UMI' or 'Gaussian' (the default is 'UMI')
                      npc = 64,                # (optional) number of PCs to keep if data_type='Gaussian' (the default is 64)
                     processed=True)

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
~/anaconda3/envs/VITAE/lib/python3.9/site-packages/VITAE/preprocess.py in preprocess(adata, processed, dimred, x, c, label_names, raw_cell_names, raw_gene_names, K, gene_num, data_type, npc, random_state)
    166         try:
--> 167             label_names = adata.obs.cell_types
    168         except:

~/anaconda3/envs/VITAE/lib/python3.9/site-packages/pandas/core/generic.py in __getattr__(self, name)
   5464                 return self[name]
-> 5465             return object.__getattribute__(self, name)
   5466 

AttributeError: 'DataFrame' object has no attribute 'cell_types'

During handling of the above exception, another exception occurred:

UnboundLocalError                         Traceback (most recent call last)
<ipython-input-12-d13f8a1785c1> in <module>
     34 
     35 # preprocess data
---> 36 model.preprocess_data(gene_num = 2000,        # (optional) maximum number of influential genes to keep (the default is 2000)
     37                      data_type = 'Gaussian', # (optional) data_type can be 'UMI', 'non-UMI' or 'Gaussian' (the default is 'UMI')
     38                       npc = 64,                # (optional) number of PCs to keep if data_type='Gaussian' (the default is 64)

~/anaconda3/envs/VITAE/lib/python3.9/site-packages/VITAE/VITAE.py in preprocess_data(self, processed, dimred, K, gene_num, data_type, npc)
    114         self.cell_names, self.gene_names, self.selected_gene_names, \
    115         self.scale_factor, self.labels, self.label_names, \
--> 116         self.le, self.gene_scalar = preprocess.preprocess(
    117             self.adata,
    118             processed,

~/anaconda3/envs/VITAE/lib/python3.9/site-packages/VITAE/preprocess.py in preprocess(adata, processed, dimred, x, c, label_names, raw_cell_names, raw_gene_names, K, gene_num, data_type, npc, random_state)
    168         except:
    169             if label_names is not None:
--> 170                 label_names = label_names[cell_mask]
    171 
    172         cell_names = adata.obs_names.values

UnboundLocalError: local variable 'cell_mask' referenced before assignment

Thank you in advance.

Best regards

jaydu1 commented 3 years ago

Hi,

For installing the latest version via pip, please use the following command.

pip install --upgrade pyvitae

Note that the option --force-reinstall you use will reinstall the current version of the installed package.

Thanks for reporting the issue. I have fixed it in v1.1.6. If there are no other issues with the preprocessing function, I'll close this one. For other problems, feel free to open new issues. Thanks.

Best.

rmathieu25 commented 3 years ago

Hello,

I have already tried this commmand line but still the 1.1.4 version is installed


!pip install --upgrade pyvitae 

Requirement already satisfied: pyvitae in /home/remi/anaconda3/envs/VITAE/lib/python3.9/site-packages (1.1.4)
Collecting pyvitae
  Using cached pyvitae-1.1.6-py3-none-any.whl (35 kB)
Requirement already satisfied: matplotlib in /home/remi/anaconda3/envs/VITAE/lib/python3.9/site-packages (from pyvitae) (3.4.2)
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import VITAE
print(VITAE.__version__)

1.1.4

Thanks.

Best regards.

jaydu1 commented 3 years ago

Hi,

Could you provide all the output information after pip install --upgrade pyvitae? Cause I didn't see the information saying that the package is installed successfully.

As shown in the following notebook: https://colab.research.google.com/drive/157macYaSIUALft6rfvD1rzzsi1XJH1Vl?usp=sharing If you install or upgrade the package successfully, you will see information like Successfully installed ... pyvitae-1.1.6 ... at the end.

Best.

rmathieu25 commented 3 years ago

Hello,

It is all that I get by upgrading.

I tried by setting a new conda environment from scratch it is still not working:

!pip install pyvitae 
Collecting pyvitae
  Using cached pyvitae-1.1.6-py3-none-any.whl (35 kB)
Collecting jupyter
  Using cached jupyter-1.0.0-py2.py3-none-any.whl (2.7 kB)
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  Using cached pyvitae-1.1.5-py3-none-any.whl (35 kB)
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Collecting seaborn
  Using cached seaborn-0.11.1-py3-none-any.whl (285 kB)
Collecting matplotlib
  Using cached matplotlib-3.4.2-cp39-cp39-manylinux1_x86_64.whl (10.3 MB)
Collecting umap-learn>=0.5.0
  Using cached umap_learn-0.5.1-py3-none-any.whl
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  Using cached ipywidgets-7.6.3-py2.py3-none-any.whl (121 kB)
Requirement already satisfied: notebook in /home/remi/anaconda3/envs/VITAE/lib/python3.9/site-packages (from jupyter->pyvitae) (6.4.0)
Requirement already satisfied: nbconvert in /home/remi/anaconda3/envs/VITAE/lib/python3.9/site-packages (from jupyter->pyvitae) (6.0.7)
Collecting qtconsole
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Requirement already satisfied: cffi>=1.0.0 in /home/remi/anaconda3/envs/VITAE/lib/python3.9/site-packages (from argon2-cffi->notebook->jupyter->pyvitae) (1.14.5)
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Collecting python-igraph>=0.9.0
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import VITAE
print(VITAE.__version__)

1.1.4

However, in Google colab it is working I have the v1.1.6

Thanks.

Best regards.

jaydu1 commented 3 years ago

I think this is not the problem with the package itself. Maybe the pip you use is not the one in the conda environment; in that case, the things may be much complicated. Maybe you can try:

pip uninstall pyvitae

and 

pip install pyvitae==1.1.6

I hope this will help.

rmathieu25 commented 3 years ago

Hello,

By recreating my conda env from scratch and dealing with some packages, I was able to install the v1.1.6 with:

pip install pyvitae==1.1.6

Thank you again.

Best regards