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We are trying to use DeepCpG on a few canine samples. We have a few normals and a few tumor samples. We wanted to know if we should be training the models on the Normals or the tumors or a mixture of both to predict the methylation status. The reason I'm asking this is we have very few normals compared to the tumor samples.
Also, once the model is trained, do we need to need to fine tune for each sample we want to call the methylation upon?
Any suggestions would be greatly helpful!
Regards,
Harish
The text was updated successfully, but these errors were encountered:
Hi!
We are trying to use DeepCpG on a few canine samples. We have a few normals and a few tumor samples. We wanted to know if we should be training the models on the Normals or the tumors or a mixture of both to predict the methylation status. The reason I'm asking this is we have very few normals compared to the tumor samples.
Also, once the model is trained, do we need to need to fine tune for each sample we want to call the methylation upon?
Any suggestions would be greatly helpful!
Regards,
Harish
The text was updated successfully, but these errors were encountered: