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I would assume the particular positions of the single mutations would also have an effect on the global variant effect. Obviously you can't model every possible interaction between the single mutations, but you could introduce a numeric variable with an unknown weight to the latent variable equation. The numeric variable would be ,say, the average distance between mutated positions for a particular variant normalized by the length of the sequence.(so it's between 0 and 1). Have such models been introduced in the literature? Would it be easy to implement in your Python library?
The text was updated successfully, but these errors were encountered:
I would assume the particular positions of the single mutations would also have an effect on the global variant effect. Obviously you can't model every possible interaction between the single mutations, but you could introduce a numeric variable with an unknown weight to the latent variable equation. The numeric variable would be ,say, the average distance between mutated positions for a particular variant normalized by the length of the sequence.(so it's between 0 and 1). Have such models been introduced in the literature? Would it be easy to implement in your Python library?
The text was updated successfully, but these errors were encountered: