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perturbench

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yanwu2014 mark-christiansen blazejosinski commited on
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update_datasets_splits (#2)

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- initial commit (cf90a37f19a47d157270e88b0cffab7378c3f66d)
- version1 (#1) (8a26d9b1f96561e6bc70856b0142c52d1c2f3ef5)
- Update README.md (45c30f31568922b0d0d6d78150974d2771443668)
- Add op3 dataset, add splits, update dataset names (3bb6a9f842172e79bfde4945a6a00e2abe19bb2f)
- Untrack readme (e4017a14b359515c00dcc22bf32a8e58003a2b37)
- Merge branch 'main' of hf.co:datasets/altoslabs/perturbench (c2468712740b3f7f2e0c43e788ce0ca42fbe3f07)
- Merge branch 'main' into pr/2 (85cf78571c360fa071364d6c081eb51ba9e35f89)
- Update README (337ea4644f1aced58ea1520d0a01d6ff3b9b522b)
- Add OP3 to readme (c7977b5cb9bc0e71ab735554afc47bc4e2cfb439)


Co-authored-by: Mark Christiansen <mark-christiansen@users.noreply.huggingface.co>
Co-authored-by: Blazej Osinski <blazejosinski@users.noreply.huggingface.co>

Files changed (14) hide show
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  3. frangieh19_preprocessed.h5ad.gz → frangieh21_processed.h5ad.gz +0 -0
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  8. mcfaline23_gxe_splits.tar.gz +3 -0
  9. norman19_cpa_hvg_normalized_curated.h5ad +3 -0
  10. norman19_cpa_hvg_normalized_splits.tar.gz +3 -0
  11. norman19_preprocessed.h5ad.gz → norman19_processed.h5ad.gz +0 -0
  12. op3_processed.h5ad.gz +3 -0
  13. op3_split.csv +3 -0
  14. srivatsan20_highest_dose_preprocessed.h5ad.gz → srivatsan20_highest_dose_processed.h5ad.gz +0 -0
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README.md CHANGED
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- ---
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- license: cc-by-4.0
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- ---
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-
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- The dataset contains data used in work:
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- "Perturbench: Benchmarking machine learning models for cellular perturbation analysis."
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-
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- The data comes from the following publications:
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-
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- - Norman, T. M., Horlbeck, M. A., Replogle, J. M., Ge, A. Y., Xu, A., Jost, M., Gilbert, L. A., and Weissman, J. S. (2019). *Exploring genetic interaction manifolds constructed from rich single-cell phenotypes.* Science, 365(6455):786–793.
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- - Srivatsan, S. R., McFaline-Figueroa, J. L., Ramani, V., Saunders, L., Cao, J., Packer, J., Pliner, H. A., Jackson, D. L., Daza, R. M., Christiansen, L., Zhang, F., Steemers, F., Shendure, J., and Trapnell, C. (2020). *Massively multiplex chemical transcriptomics at single-cell resolution.* Science, 367(6473):45–51.
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- - Frangieh, C. J., Melms, J. C., Thakore, P. I., Geiger-Schuller, K. R., Ho, P., Luoma, A. M., Cleary, B., Jerby-Arnon, L., Malu, S., Cuoco, M. S., Zhao, M., Ager, C. R., Rogava, M., Hovey,
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- L., Rotem, A., Bernatchez, C., Wucherpfennig, K. W., Johnson, B. E., Rozenblatt-Rosen, O.,
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- Schadendorf, D., Regev, A., and Izar, B. (2021). *Multimodal pooled Perturb-CITE-seq screens in
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- patient models define mechanisms of cancer immune evasion*. Nat. Genet., 53(3):332–341.
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- - Jiang, L., Dalgarno, C., Papalexi, E., Mascio, I., Wessels, H.-H., Yun, H., Iremadze, N., Lithwick Yanai, G., Lipson, D., and Satija, R. (2024a). *Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens.* bioRxiv, page 2024.01.29.576933.
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- - McFaline-Figueroa, J. L., Srivatsan, S., Hill, A. J., Gasperini, M., Jackson, D. L., Saunders,
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- L., Domcke, S., Regalado, S. G., Lazarchuck, P., Alvarez, S., et al.
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- (2024). *Multiplex single cell chemical genomics reveals the kinase dependence of the response to targeted therapy*. Cell Genomics, 4(2)
 
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