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Added PertEval-scFM #78

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Jan 28, 2025
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8 changes: 4 additions & 4 deletions _data/transformer-evaluation.yml
Original file line number Diff line number Diff line change
@@ -77,10 +77,10 @@
type: 'reproducible'
text: '[ð\x9F\x9B\_ï¸\x8FGitHub](https://github.com/aaronwtr/PertEval)'
url: 'https://github.com/aaronwtr/PertEval'
omic_modalities: '-'
evaluated_transformers: '-'
tasks: '-'
notes: '-'
omic_modalities: 'scRNA-seq'
evaluated_transformers: 'UCE, scBERT, scGPT, Geneformer, scFoundation'
tasks: 'Transcriptomic perturbation prediction'
notes: 'Introduces PertEval-scFM, a benchmark to assess the zero-shot utility of single-cell foundation model embeddings for transcriptomic perturbation prediction. Uses SPECTRA to generate train-test splits with increasing dissimilarity to evaluate robustness against distribution shift. Models are evaluated with MSE and AUSPC, with AUSPC reflecting robustness under distribution shift. Additional analyses include E-distance and predicted transcriptomic distributions across the top 20 DEGs. Findings suggest that single-cell foundation model embeddings capture average perturbation effects but generally lack robustness to distribution shift. Ongoing work demonstrates that the domain-specific model GEARS outperforms foundation model embeddings, indicating that masked-language modeling on gene expression data without domain-specific inductive biases is insufficient for accurate transcriptomic perturbation prediction.'