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Paulos2411 authored Jan 21, 2025
2 parents b0a7508 + c8387f4 commit 3bc51e4
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evaluated_transformers: scGPT, Geneformer, scBERT
tasks: Cell type annotation
notes: Focused on imbalanced cell type classification. Geneformer appears to be outperformed by scGPT and scBERT, where the two latter perform similarly.
- paper:
type: preprint
text: '[Csendes et al. 2024](https://www.biorxiv.org/content/10.1101/2024.09.30.615843v1)'
url: https://www.biorxiv.org/content/10.1101/2024.09.30.615843v1
code:
type: reproducible
text: "\x9F\x9B\_ï¸\x8FGitHub](https://github.com/turbine-ai/PerturbSeqPredBenchmark)"
url: https://github.com/turbine-ai/PerturbSeqPredBenchmark
omic_modalities: scRNA-seq
evaluated_transformers: scGPT
tasks: Genetic perturbation effect prediction
notes: Simple baseline models can outperform scGPT on perturbational downstream tasks. The most widely used benchmarking datasets contain significant biases, making them suboptimal for evaluation.

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