Inference

[raphaelmourad]

Thanks for the work!

How can I use your model finetuned on tahoe for instance to predict the gene expression matrix of cells perturbed by a drug given my own gene expression matrix of control cells? That would a very useful notebook to have :).
Raf

[KatarinaYuan]

Hi,
Thanks for the great suggestion! We haven't tested this "one data to another data" finetuning transfer before.
One naive way is to directly load the pretrained tahoe ckpt via model.ckpt_path=/path/to/ckpt, but it might require some minor fixed if the metadata vocabulary (e.g., drugs, cell lines) of your data does not match that of Tahoe100M.

Another important thing is that diffusion framework needs early stopping even for training from scratch on one dataset. Finetuning might face similar issues.

Which dataset (if it's public) you use? I can try to create some small demo for it.

[raphaelmourad]

Hi Katarina,
I do believe if you implement this predictions it would be very valuable as Stack did (they predicted all perturbed data from unperturbed data from tabula sapiens). At the end they got all drug induced perturbed data for all cells from tabula sapiens. What would be awesome would be to make a script to predict any perturbation in tahoe (a given drug at a given perturbation) on unperturbed data from tabula sapiens. For instance, you can take skin data such as : https://datasets.cellxgene.cziscience.com/88930108-9c98-43a7-826d-ce454dd0c930.h5ad
Here the idea is to not make any finetuning. Just take your a model trained on tahoe and take as input an unperturbed data and predict a perturbed data as state and stack do.
I can assure you that many people would want to use this script !!
Raf

[KatarinaYuan]

Hi,
Sorry for the late response (too busy last few weeks). Let me look into this.