Comments (8)
Here's the result of my final visualization
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Hello!
I encountered an error when running the 9th cell, which said "items in new_categories are not the same as in old categories." When I tried to change the order of the celltype defined by the original author to match the new_categories in order to solve this problem, I found that the result was the same as the one you obtained in the running result. Did you encounter the same error as well?
And,if you are also a Chinese student, perhaps we can further communicate .
from tosica.
Hello! I encountered an error when running the 9th cell, which said "items in new_categories are not the same as in old categories." When I tried to change the order of the celltype defined by the original author to match the new_categories in order to solve this problem, I found that the result was the same as the one you obtained in the running result. Did you encounter the same error as well? And,if you are also a Chinese student, perhaps we can further communicate .
Yes, I'm getting the same error
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Hi! I encountered similar error as you guys. Solved as what [apologize66] did, I got a different result but still very different from the original celltype with relatively low accuracy.
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Hi! I encountered similar error as you guys. Solved as what [apologize66] did, I got a different result but still very different from the original celltype with relatively low accuracy.
I tried to useTOSICA to train my own model with human lung scRNA-seq dataset using epoch=20. The validate accuracy is 0.993 when training the model. But when I used the model to predict internal test dataset, the accuracy is only about 0.29. I don't know why.
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Thank you for your interest in TOSICA.
Unfortunately I cannot judge where the problem is from what has been shown here. If I encounter this problem, first, I will check whether the var_names
of the ref_adata and query_adata are consistent and in the same order. Then I will check whether the pre-trained model is loaded correctly.
Besides, I noticed that different cell types were correctly separated in the attention space and there is no cell were predict to be alpha cell which is the most abundant cell type and should have the highest prediction accuracy. So I'm worried if there's something wrong with label_dictionary.csv
.
If the prediction is still terrible and you are willing to share your demo dataset and code, I would be happy to help you analyze and examine what happened here!
from tosica.
Hello! I encountered an error when running the 9th cell, which said "items in new_categories are not the same as in old categories." When I tried to change the order of the celltype defined by the original author to match the new_categories in order to solve this problem, I found that the result was the same as the one you obtained in the running result. Did you encounter the same error as well? And,if you are also a Chinese student, perhaps we can further communicate .
Maybe, you masked alpha cells in the traing process, which resulted in the categories of predicted cell types being different from those in the tutorial.ipynb
.
I am glad to have more communications, here is my email: [email protected] and wechat: chenjiawei9667
from tosica.
Hi! I encountered similar error as you guys. Solved as what [apologize66] did, I got a different result but still very different from the original celltype with relatively low accuracy.
Thank you for your interest in TOSICA.
Similarly, I noticed that different cell types were correctly separated and there is no cell were predict to be alpha cell which is the most abundant cell type and should have the highest prediction accuracy. perhaps you masked alpha cells in the traing process, but the default cutoff of the predction is 0.1 which will resulte in a low accuracy.
As for the human lung scRNA-seq dataset, I am glad to help you analyze and examine what happened.
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Related Issues (19)
- Share test data file in the tutorial HOT 1
- Sharing code to reproduce manuscript figures HOT 1
- Quick question about prediction result HOT 3
- What will happen if the number or order of var_names is different? HOT 3
- [bug] There is a bug when I install the software HOT 2
- could you share what's hardware(GPU) used to train this model? HOT 2
- Questions about reading certain datasets HOT 1
- could you share the other 5 datasets detailed preprocessing codes HOT 1
- model depth=2, cause more 8 times GPU usage than depth=1 in hPancreas dataset train HOT 3
- TOSICA install problem HOT 1
- use TOSICA for cell classification HOT 4
- Problem with TOSICA metrics comparing HOT 1
- Cannot import TOSICA due to issue with np.long HOT 3
- Memory leakage HOT 3
- Data preprocessing HOT 1
- Code Consulting HOT 1
- TOSICA pre function gives very different accuracy than evaluate in train function HOT 2
- Mask matrix issues HOT 1
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