`.X`. error using sct.train.Trainer() about sctour HOT 11 OPEN

Hi,
Please run adata = adata.raw.to_adata() to get raw counts in adata.X before all steps as both the sc.pp.highly_variable_genes (when using flavor='seurat_v3') and scTour under default mode expect raw UMI counts. Please let me know if you have any further questions.

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@LiQian-XC

Thanks for your fast response. When running run adata = adata.raw.to_adata() at the beginning, it encounters a new error as follows:

tnode = sct.train.Trainer(adata, loss_mode='nb', alpha_recon_lec=0.5, alpha_recon_lode=0.5)
tnode.train()

Running using CPU.

AttributeError Traceback (most recent call last)
Cell In[16], line 2
1 tnode = sct.train.Trainer(adata, loss_mode='nb', alpha_recon_lec=0.5, alpha_recon_lode=0.5)
----> 2 tnode.train()

File ~/.../sctour/lib/python3.10/site-packages/sctour/train.py:258, in Trainer.train(self)
254 def train(self):
255 """
256 Model training.
257 """
--> 258 self._get_data_loaders()
260 params = filter(lambda p: p.requires_grad, self.model.parameters())
261 self.optimizer = torch.optim.Adam(params, lr = self.lr, weight_decay = self.wt_decay, eps = self.eps)

File ~/.../sctour/lib/python3.10/site-packages/sctour/train.py:245, in Trainer._get_data_loaders(self)
240 """
241 Generate Data Loaders for training and validation datasets.
242 """
244 train_data, val_data = split_data(self.adata, self.percent, self.val_frac)
--> 245 self.train_dataset = MakeDataset(train_data, self.loss_mode)
246 self.val_dataset = MakeDataset(val_data, self.loss_mode)
248 # sampler = BatchSampler(train_data.n_obs, self.batch_size, self.drop_last)
249 # self.train_dl = DataLoader(self.train_dataset, batch_sampler = sampler)

File ~/miniconda3/envs/sctour/lib/python3.10/site-packages/sctour/data.py:99, in MakeDataset.init(self, adata, loss_mode)
97 X = np.log1p(X)
98 if sparse.issparse(X):
---> 99 X = X.A
100 self.data = torch.tensor(X)
101 self.library_size = self.data.sum(-1)

AttributeError: 'SparseCSRView' object has no attribute 'A'

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Hi,

Can you try the following steps to see whether it works?

from scipy.sparse import csr_matrix
adata.X = csr_matrix(adata.X)

Please let me know if you have any other questions.

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@LiQian-XC
After running
from scipy.sparse import csr_matrix
adata.X = csr_matrix(adata.X),
the same issue persisted. However, I tried using adata.X = adata.X.toarray() later, and it solved the problem. Thank you for your prompt response.

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@LiQian-XC : we are having what I assume is an analogous issue. I was the

AttributeError: 'SparseCSRView' object has no attribute 'X' error just like above, when calling train(). The csr_matrix() solution did not work. FWIW, our code is subsetting the adata object right before training, and I suspect this is converting into this this View class:

adataObj = adataObj[:, list(set(adataObj.var_names) - set(exclusionList))]
tnode = sct.train.Trainer(adataObj)

My guess is that something about sutsetting is converting the AnnData object into a view of the data, and that isnt interacting well with scTour. Do you have any debugging suggestions or tests on the anndata object to verify that theory?

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Hi,

Can you try to copy the data when subsetting (please see your example below)?

adataObj = adataObj[:, list(set(adataObj.var_names) - set(exclusionList))].copy()

I think this may address this issue and please let me know if it does not work.

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Thanks for the idea. Yes, after posting I came to the same conclusion. Tests are running on the code here: https://github.com/bimberlabinternal/CellMembrane/blob/407adf4f1d998af41c1de79f257e94bfe256d0ee/inst/scripts/run_sctour.py#L31

If this is a solution, would you consider adding this kind of test directly to scTour?

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Thanks for sharing your code. I will consider adding this in a new version of scTour.

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Hi everyone,

The solution @pandaqiuqiu pointed out works for this error as well. Scipy stopped supporting .A as a shorthand for .toarray() in 1.14 (released Jun 24th, https://docs.scipy.org/doc/scipy/release/1.14.0-notes.html#expired-deprecations).

To support scipy >= 1.14, changing

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To be clear, I think there's two total lines of code, the one above and this that would need to be changed:

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Thank you all for pointing this out. I will fix it and release a new version.

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