I have 2 batches (B1 and B2), in each batch I have 5 samples (B1_X1, B1_X2, B1_X3, B1_X4, B1_X5) (B2_X1, B2_X2, B2_X6, B2_X7, B2_X8)
I have only X1 and X2 in common between B1 and B2.
I know that B1 is good, the staining in B2 was not perfect for some markers. I want to correct the staining in B2 to look like the staining in B1.
Should I only use X1 and X2 to train my model and then use the model to normalize X6,X7,X8?
How do I specify that B1 is good and that I want B2 to be corrected and not the opposite?
Hello everyone,
I have 2 batches (B1 and B2), in each batch I have 5 samples (B1_X1, B1_X2, B1_X3, B1_X4, B1_X5) (B2_X1, B2_X2, B2_X6, B2_X7, B2_X8) I have only X1 and X2 in common between B1 and B2. I know that B1 is good, the staining in B2 was not perfect for some markers. I want to correct the staining in B2 to look like the staining in B1. Should I only use X1 and X2 to train my model and then use the model to normalize X6,X7,X8? How do I specify that B1 is good and that I want B2 to be corrected and not the opposite?
Thank you a lot for your feedback!