Model
Geneformer is a tabular count model trained on sc-RNA from the Chan Zuckerberg Cell x Gene census
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| Field | Response |
|---|---|
| Intended Application(s) & Domain(s): | Generates representations of cells from genes |
| Model Type: | Gene Expression Representation |
| Intended Users: | This model is intended for academic and industrial computational biologists who study and perform experiments with single cell RNA sequencing data. |
| Outputs: | Gene Expression Embeddings |
| Describe how the model works: | Outputs a dense embedding based on masked genes and classification targets. |
| Technical Limitations: | The model does not take into account the magnitude of gene expression, only the rank. The model is technically limited to only observing 1000-2000 genes rather than the entire set of possible targets (~20,000). |
| Verified to have met prescribed NVIDIA standards: | Yes |
| Performance Metrics: | * Reconstruction Error (Cross Entropy) * Cell Type Classification |
| Potential Known Risks: | The model may not work on cell types and genes unrelated to neuronal gene expression; model accuracy should be further researched for potential differences in population based on age, sex, and ethnicity. |
| Licensing: | Apache 2.0 |