Comments (3)
Hi pvtodorov,
I am sorry the URL with the team repos yields a 404: it's for Broad Institute only and I did not realize that.
Yes, we uploaded the code for the NN shortly after your request: you can find the code here:
https://github.com/broadinstitute/one-shot-atlas
In this repo you'll find the code of our Siamese although you'll notice that we have not released our training set yet. We will do that after the paper is published.
To make sure we are on the same page: our NN fetches the mouse brain image at the corresponding depth. This is our first step our pipeline. The second is to generate masks using a U-net model (we use this one https://github.com/qubvel/segmentation_models). Again, we will release the training set with the labels soon (probably after the paper is published). To register the masks, we use ANTs (see here http://stnava.github.io/ANTs/).
Therefore, our NN does not do end-to-end registration. If you are looking for a DL model for doing that, I recommend you check out voxelmorph (https://github.com/voxelmorph/voxelmorph).
Ciao,
from tangram.
Tangram is, strictly speaking, the algorithm for mapping, but the NN will be available soon (ie tomorrow at the latest).
Keep an eye out on our team repos: https://github.com/orgs/broadinstitute/teams/tommaso_team/
We will make public a new repo soon.
from tangram.
Just wanted to check if the repo was ever updated - the provided link comes up as a 404
Totally understand if there has been a delay!
from tangram.
Related Issues (20)
- Can we have an API as batch size for the integration method? HOT 3
- No attribute 'pp_adatas' in tangram HOT 2
- Possible to use multiple single cell datasets in Tangram? HOT 3
- Cannot find correspondence of the input data HOT 1
- question about training genes HOT 1
- Some questions about best practices HOT 1
- Attribute error : module 'tangram' has no attribute 'map_cells_to_space' HOT 2
- scRNAseq cells < spatial cells, curious about how mapping works HOT 3
- Unexpected behaviour HOT 1
- Question about acceptable AUC, improving AUC HOT 1
- potential overfitting HOT 5
- Interpretation of tangram_ct_pred HOT 2
- Option "enforce gene lowercase" HOT 1
- error when sq.im.segment
- Tangram Deconvolution HOT 1
- Using Integrated single cell data for alignment
- AttributeError: module 'tangram' has no attribute 'pp_adatas'
- Sparsity_sc and sparsity_sp = 0
- Please explain `project_cell_annotations`
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from tangram.