Add study-trained SCimilarity checkpoints

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: e1a3739a-1ad6-4a7d-9531-11fb3cc268f7

.gitattributes

@@ -1,9 +1,11 @@
 *.safetensors filter=lfs diff=lfs merge=lfs -text
 *.npy filter=lfs diff=lfs merge=lfs -text
 *.pkl filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
 *.json text eol=lf
 *.csv text eol=lf
 *.py text eol=lf
 *.md text eol=lf
 *.txt text eol=lf
 *.cff text eol=lf
+*.tsv text eol=lf

.gitignore

@@ -12,5 +12,7 @@ download-receipts.json
 model-validation*.json
 *.partial
 *.ckpt
+!portable-checkpoints/scimilarity/**/encoder.ckpt
+!portable-checkpoints/scimilarity/**/decoder.ckpt
 *.pt
 wandb/

README.md

@@ -6,6 +6,7 @@ tags:
   - geneformer
   - scvi
   - self-supervised-learning
+  - scimilarity
   - pca
   - safetensors
 inference: false
@@ -27,20 +28,27 @@ DenAdel et al., *Nature Methods* (2026).
 | Geneformer | 125 |
 | scVI | 125 |
 | SSL/MLP | 125 |
+| SCimilarity | 80 |
 | PCA components | 80 |
-| **Total** | **455** |
+| **Total** | **535** |
 
-The full download is approximately **22.4 GB**: 375 neural network checkpoints
+The full download is approximately **36.5 GB**: 455 neural network checkpoints
 and 80 PCA component matrices.
 
 Within `portable-checkpoints/`, models are grouped into `geneformer/`,
-`scvi/`, `ssl/` and `pca/`.
+`scvi/`, `ssl/`, `scimilarity/` and `pca/`.
 
 The Geneformer, scVI and SSL models cover random sampling, cell-type
 reweighting and geometric sketching at 1, 10, 25, 50, 75 and 100 percent of
 the pretraining corpus. The collection also includes perturbation spike-in
 experiments. See `model-index.csv` for model folders and training settings.
 
+SCimilarity includes five seeds at each of 1, 10, 25, 50 and 75 percent for
+`random`, `celltype_reweighted` and `geometric_sketching` sampling, plus five
+100-percent random models. Each folder contains the native encoder and
+decoder weights, gene order, layer sizes and cell-type labels. These are
+study-trained models, not the upstream SCimilarity pretrained models.
+
 ## Download
 
 Use Python **3.10**. The examples below were tested on CPU.
@@ -63,6 +71,8 @@ python -m pip install -r requirements.txt
 To download individual models, use `allow_patterns` with the model folders
 listed in `model-index.csv`. Include `model-index.csv`, `tools/*`,
 `public-resources/*` and `requirements.txt` to use the loading code below.
+For SCimilarity alone, PyTorch is sufficient; download the model's five files
+and `tools/*.py`. No cell-search database is included or required.
 
 ## Load a checkpoint
 
@@ -90,6 +100,13 @@ ssl = load_model("portable-checkpoints/ssl/random/idx_100pct_seed25")
 with torch.no_grad():
     latent, reconstruction = ssl(torch.ones(2, 19331))
 
+scimilarity = load_model(
+    "portable-checkpoints/scimilarity/random/idx_100pct_seed25"
+)
+with torch.no_grad():
+    embedding, reconstruction = scimilarity(torch.ones(2, scimilarity.n_genes))
+    # Embeddings have shape (2, 128); reconstructions have shape (2, 19331).
+
 pca_row = next(row for row in rows if row["family"] == "PCA")
 components = load_model(pca_row["portable_directory"])
 projection = np.ones((2, 19331), dtype=components.dtype) @ components
@@ -100,6 +117,14 @@ ranked gene inputs and normalization using the tokenizer dictionaries in
 `public-resources/geneformer/`. SSL and PCA use the paper's 19,331-gene
 scTab order.
 
+SCimilarity takes expression values aligned to `scimilarity.gene_order`
+(also in each model's `gene_order.tsv`), normalized to 10,000 counts per cell
+and transformed with `log1p`. Its encoder returns L2-normalized embeddings.
+Use `scimilarity.encoder(expression)` when only embeddings are needed;
+`scimilarity.decoder(embedding)` returns reconstructed log-normalized values,
+not raw counts. The bundled network classes are from SCimilarity 0.4.1 and
+do not require its atlas/search dependencies.
+
 For scVI, provide an AnnData object with raw counts in `X` and `var_names`
 matching the `gene_names` order in the model's `config.json`.
 
@@ -114,8 +139,9 @@ latent = scvi_model.get_latent_representation()
 ## License
 
 The model weights, PCA components and loading code are licensed under
-**MIT**. Geneformer tokenizer files use **Apache-2.0**, and the included SSL
-code uses MIT. See `LICENSE` and `THIRD_PARTY_NOTICES.md` for the full terms
+**MIT**, except for the bundled SCimilarity network implementation, which
+uses **Apache-2.0**. Geneformer tokenizer files also use Apache-2.0, and the
+included SSL code uses MIT. See `LICENSE` and `THIRD_PARTY_NOTICES.md` for the full terms
 and copyright notices.
 
 ## Citation

THIRD_PARTY_NOTICES.md

@@ -1,7 +1,7 @@
 # Third-party notices
 
-The study weights, PCA components and loading code use the MIT license in
-`LICENSE`, with the Microsoft copyright notice. Third-party files retain
+The study weights, PCA components and loading adapters use the MIT license
+in `LICENSE`, with the Microsoft copyright notice. Third-party files retain
 the licenses and copyright notices listed below.
 
 ## Paper code and gene order
@@ -36,6 +36,17 @@ The loading adapters in `tools/` use these source files to construct the models.
 The Geneformer weights are models trained for this study, not upstream
 Geneformer pretrained weights.
 
+## SCimilarity network implementation
+
+- Project: https://github.com/Genentech/scimilarity
+- Included source: `tools/_scimilarity_networks.py`, the unmodified
+  `scimilarity/nn_models.py` from version 0.4.1.
+- License: Apache-2.0, Copyright 2023 Genentech, Inc.
+- Full notice and terms: `licenses/SCimilarity-Apache-2.0.txt`.
+
+The SCimilarity encoder and decoder weights were trained for this study;
+they are distributed under MIT, separately from the upstream implementation.
+
 ## Dependencies and data
 
 Runtime packages are installed separately and retain their own licenses.

licenses/SCimilarity-Apache-2.0.txt

@@ -0,0 +1,217 @@
+Copyright 2023 Genentech, Inc.
+
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+See the License for the specific language governing permissions and
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+
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model-index.csv

@@ -454,3 +454,83 @@ PCA,random,75.0,21,pca,portable-checkpoints/pca/random/idx_75pct_seed21,idx_75pc
 PCA,random,75.0,22,pca,portable-checkpoints/pca/random/idx_75pct_seed22,idx_75pct_seed22_TRAIN
 PCA,random,75.0,23,pca,portable-checkpoints/pca/random/idx_75pct_seed23,idx_75pct_seed23_TRAIN
 PCA,random,75.0,24,pca,portable-checkpoints/pca/random/idx_75pct_seed24,idx_75pct_seed24_TRAIN
+SCimilarity,celltype_reweighted,10,5,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_10pct_seed5,encoder_decoder_export
+SCimilarity,celltype_reweighted,10,6,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_10pct_seed6,encoder_decoder_export
+SCimilarity,celltype_reweighted,10,7,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_10pct_seed7,encoder_decoder_export
+SCimilarity,celltype_reweighted,10,8,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_10pct_seed8,encoder_decoder_export
+SCimilarity,celltype_reweighted,10,9,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_10pct_seed9,encoder_decoder_export
+SCimilarity,celltype_reweighted,1,0,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed0,encoder_decoder_export
+SCimilarity,celltype_reweighted,1,1,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed1,encoder_decoder_export
+SCimilarity,celltype_reweighted,1,2,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed2,encoder_decoder_export
+SCimilarity,celltype_reweighted,1,3,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed3,encoder_decoder_export
+SCimilarity,celltype_reweighted,1,4,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed4,encoder_decoder_export
+SCimilarity,celltype_reweighted,25,10,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_25pct_seed10,encoder_decoder_export
+SCimilarity,celltype_reweighted,25,11,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_25pct_seed11,encoder_decoder_export
+SCimilarity,celltype_reweighted,25,12,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_25pct_seed12,encoder_decoder_export
+SCimilarity,celltype_reweighted,25,13,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_25pct_seed13,encoder_decoder_export
+SCimilarity,celltype_reweighted,25,14,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_25pct_seed14,encoder_decoder_export
+SCimilarity,celltype_reweighted,50,15,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_50pct_seed15,encoder_decoder_export
+SCimilarity,celltype_reweighted,50,16,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_50pct_seed16,encoder_decoder_export
+SCimilarity,celltype_reweighted,50,17,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_50pct_seed17,encoder_decoder_export
+SCimilarity,celltype_reweighted,50,18,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_50pct_seed18,encoder_decoder_export
+SCimilarity,celltype_reweighted,50,19,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_50pct_seed19,encoder_decoder_export
+SCimilarity,celltype_reweighted,75,20,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_75pct_seed20,encoder_decoder_export
+SCimilarity,celltype_reweighted,75,21,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_75pct_seed21,encoder_decoder_export
+SCimilarity,celltype_reweighted,75,22,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_75pct_seed22,encoder_decoder_export
+SCimilarity,celltype_reweighted,75,23,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_75pct_seed23,encoder_decoder_export
+SCimilarity,celltype_reweighted,75,24,main,portable-checkpoints/scimilarity/celltype_reweighted/idx_75pct_seed24,encoder_decoder_export
+SCimilarity,geometric_sketching,10,5,main,portable-checkpoints/scimilarity/geometric_sketching/idx_10pct_seed5,encoder_decoder_export
+SCimilarity,geometric_sketching,10,6,main,portable-checkpoints/scimilarity/geometric_sketching/idx_10pct_seed6,encoder_decoder_export
+SCimilarity,geometric_sketching,10,7,main,portable-checkpoints/scimilarity/geometric_sketching/idx_10pct_seed7,encoder_decoder_export
+SCimilarity,geometric_sketching,10,8,main,portable-checkpoints/scimilarity/geometric_sketching/idx_10pct_seed8,encoder_decoder_export
+SCimilarity,geometric_sketching,10,9,main,portable-checkpoints/scimilarity/geometric_sketching/idx_10pct_seed9,encoder_decoder_export
+SCimilarity,geometric_sketching,1,0,main,portable-checkpoints/scimilarity/geometric_sketching/idx_1pct_seed0,encoder_decoder_export
+SCimilarity,geometric_sketching,1,1,main,portable-checkpoints/scimilarity/geometric_sketching/idx_1pct_seed1,encoder_decoder_export
+SCimilarity,geometric_sketching,1,2,main,portable-checkpoints/scimilarity/geometric_sketching/idx_1pct_seed2,encoder_decoder_export
+SCimilarity,geometric_sketching,1,3,main,portable-checkpoints/scimilarity/geometric_sketching/idx_1pct_seed3,encoder_decoder_export
+SCimilarity,geometric_sketching,1,4,main,portable-checkpoints/scimilarity/geometric_sketching/idx_1pct_seed4,encoder_decoder_export
+SCimilarity,geometric_sketching,25,10,main,portable-checkpoints/scimilarity/geometric_sketching/idx_25pct_seed10,encoder_decoder_export
+SCimilarity,geometric_sketching,25,11,main,portable-checkpoints/scimilarity/geometric_sketching/idx_25pct_seed11,encoder_decoder_export
+SCimilarity,geometric_sketching,25,12,main,portable-checkpoints/scimilarity/geometric_sketching/idx_25pct_seed12,encoder_decoder_export
+SCimilarity,geometric_sketching,25,13,main,portable-checkpoints/scimilarity/geometric_sketching/idx_25pct_seed13,encoder_decoder_export
+SCimilarity,geometric_sketching,25,14,main,portable-checkpoints/scimilarity/geometric_sketching/idx_25pct_seed14,encoder_decoder_export
+SCimilarity,geometric_sketching,50,15,main,portable-checkpoints/scimilarity/geometric_sketching/idx_50pct_seed15,encoder_decoder_export
+SCimilarity,geometric_sketching,50,16,main,portable-checkpoints/scimilarity/geometric_sketching/idx_50pct_seed16,encoder_decoder_export
+SCimilarity,geometric_sketching,50,17,main,portable-checkpoints/scimilarity/geometric_sketching/idx_50pct_seed17,encoder_decoder_export
+SCimilarity,geometric_sketching,50,18,main,portable-checkpoints/scimilarity/geometric_sketching/idx_50pct_seed18,encoder_decoder_export
+SCimilarity,geometric_sketching,50,19,main,portable-checkpoints/scimilarity/geometric_sketching/idx_50pct_seed19,encoder_decoder_export
+SCimilarity,geometric_sketching,75,20,main,portable-checkpoints/scimilarity/geometric_sketching/idx_75pct_seed20,encoder_decoder_export
+SCimilarity,geometric_sketching,75,21,main,portable-checkpoints/scimilarity/geometric_sketching/idx_75pct_seed21,encoder_decoder_export
+SCimilarity,geometric_sketching,75,22,main,portable-checkpoints/scimilarity/geometric_sketching/idx_75pct_seed22,encoder_decoder_export
+SCimilarity,geometric_sketching,75,23,main,portable-checkpoints/scimilarity/geometric_sketching/idx_75pct_seed23,encoder_decoder_export
+SCimilarity,geometric_sketching,75,24,main,portable-checkpoints/scimilarity/geometric_sketching/idx_75pct_seed24,encoder_decoder_export
+SCimilarity,random,100,25,main,portable-checkpoints/scimilarity/random/idx_100pct_seed25,encoder_decoder_export
+SCimilarity,random,100,26,main,portable-checkpoints/scimilarity/random/idx_100pct_seed26,encoder_decoder_export
+SCimilarity,random,100,27,main,portable-checkpoints/scimilarity/random/idx_100pct_seed27,encoder_decoder_export
+SCimilarity,random,100,28,main,portable-checkpoints/scimilarity/random/idx_100pct_seed28,encoder_decoder_export
+SCimilarity,random,100,29,main,portable-checkpoints/scimilarity/random/idx_100pct_seed29,encoder_decoder_export
+SCimilarity,random,10,5,main,portable-checkpoints/scimilarity/random/idx_10pct_seed5,encoder_decoder_export
+SCimilarity,random,10,6,main,portable-checkpoints/scimilarity/random/idx_10pct_seed6,encoder_decoder_export
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+SCimilarity,random,10,8,main,portable-checkpoints/scimilarity/random/idx_10pct_seed8,encoder_decoder_export
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portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed1/layer_sizes.json

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portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed2/decoder.ckpt

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portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed2/encoder.ckpt

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portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed2/label_ints.csv

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+"",0
+0,"inflammatory macrophage"
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+2,"alveolar macrophage"
+3,"epithelial cell of proximal tubule"
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+6,"ependymal cell"
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+8,"mature NK T cell"
+9,"pulmonary artery endothelial cell"
+10,"oligodendrocyte"
+11,"mature B cell"
+12,"intestine goblet cell"
+13,"microglial cell"
+14,"Schwann cell"
+15,"smooth muscle cell"
+16,"capillary endothelial cell"
+17,"erythrocyte"
+18,"immature innate lymphoid cell"
+19,"kidney collecting duct intercalated cell"
+20,"kidney distal convoluted tubule epithelial cell"
+21,"hematopoietic stem cell"
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+25,"CD8-positive, alpha-beta memory T cell"
+26,"IgG plasma cell"
+27,"megakaryocyte-erythroid progenitor cell"
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+29,"endothelial cell"
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+34,"T-helper 17 cell"
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+37,"retinal cone cell"
+38,"CD16-positive, CD56-dim natural killer cell, human"
+39,"vascular associated smooth muscle cell"
+40,"CD14-low, CD16-positive monocyte"
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+44,"dendritic cell"
+45,"CD14-positive monocyte"
+46,"IgA plasma cell"
+47,"lymphocyte"
+48,"keratinocyte"
+49,"pericyte"
+50,"alternatively activated macrophage"
+51,"enteroendocrine cell"
+52,"luminal epithelial cell of mammary gland"
+53,"blood vessel endothelial cell"
+54,"leukocyte"
+55,"central memory CD4-positive, alpha-beta T cell"
+56,"promonocyte"
+57,"enterocyte"
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+59,"activated CD4-positive, alpha-beta T cell"
+60,"double negative T regulatory cell"
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+62,"regulatory T cell"
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+91,"amacrine cell"
+92,"CD8-positive, alpha-beta cytotoxic T cell"
+93,"CD4-positive, alpha-beta cytotoxic T cell"
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+95,"conventional dendritic cell"
+96,"CD4-positive helper T cell"
+97,"B cell"
+98,"retinal rod cell"
+99,"tracheobronchial smooth muscle cell"
+100,"mucosal invariant T cell"
+101,"transitional stage B cell"
+102,"respiratory basal cell"
+103,"kidney loop of Henle thin descending limb epithelial cell"
+104,"kidney connecting tubule epithelial cell"
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+106,"basal cell"
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+108,"retina horizontal cell"
+109,"alpha-beta T cell"
+110,"CD8-positive, alpha-beta T cell"
+111,"effector CD8-positive, alpha-beta T cell"
+112,"kidney interstitial fibroblast"
+113,"effector memory CD4-positive, alpha-beta T cell"
+114,"goblet cell"
+115,"mesothelial cell"
+116,"gamma-delta T cell"
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+118,"fibroblast of cardiac tissue"
+119,"lymphoid lineage restricted progenitor cell"
+120,"platelet"
+121,"T follicular helper cell"
+122,"neutrophil"
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+124,"plasmacytoid dendritic cell"
+125,"CD16-negative, CD56-bright natural killer cell, human"
+126,"enteric smooth muscle cell"
+127,"class switched memory B cell"
+128,"CD4-positive, alpha-beta memory T cell"
+129,"effector memory CD8-positive, alpha-beta T cell"
+130,"tracheal goblet cell"
+131,"exhausted T cell"

portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed2/layer_sizes.json

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portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed3/decoder.ckpt

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portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed3/encoder.ckpt

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portable-checkpoints/scimilarity/celltype_reweighted/idx_1pct_seed3/label_ints.csv

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+"",0
+0,"pulmonary artery endothelial cell"
+1,"renal interstitial pericyte"
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+3,"activated CD4-positive, alpha-beta T cell"
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+18,"mature NK T cell"
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+20,"hematopoietic stem cell"
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+23,"naive T cell"
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+25,"CD8-positive, alpha-beta memory T cell"
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+28,"keratinocyte"
+29,"enteroendocrine cell"
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+33,"effector memory CD4-positive, alpha-beta T cell"
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+36,"microglial cell"
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+38,"exhausted T cell"
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+42,"macrophage"
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+45,"memory T cell"
+46,"plasmablast"
+47,"kidney loop of Henle thin ascending limb epithelial cell"
+48,"neuron"
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+51,"transitional stage B cell"
+52,"basal cell"
+53,"effector memory CD8-positive, alpha-beta T cell"
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+57,"CD8-positive, alpha-beta T cell"
+58,"lymphocyte"
+59,"kidney distal convoluted tubule epithelial cell"
+60,"CD16-positive, CD56-dim natural killer cell, human"
+61,"fibroblast of cardiac tissue"
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+63,"oligodendrocyte"
+64,"plasmacytoid dendritic cell"
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+66,"T follicular helper cell"
+67,"Bergmann glial cell"
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+91,"kidney connecting tubule epithelial cell"
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+104,"erythroblast"
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+106,"amacrine cell"
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+108,"paneth cell"
+109,"alveolar macrophage"
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+111,"goblet cell"
+112,"vascular associated smooth muscle cell"
+113,"B cell"
+114,"precursor B cell"
+115,"enteric smooth muscle cell"
+116,"retinal cone cell"
+117,"retina horizontal cell"
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+122,"naive B cell"
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+124,"kidney interstitial fibroblast"
+125,"CD4-positive helper T cell"
+126,"central nervous system macrophage"
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+128,"endothelial cell"
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+130,"CD1c-positive myeloid dendritic cell"
+131,"effector CD8-positive, alpha-beta T cell"
+132,"luminal epithelial cell of mammary gland"