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--- |
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license: mit |
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tags: |
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- biology |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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dataset_info: |
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features: |
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- name: counts |
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sequence: int32 |
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- name: counts_norm |
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sequence: float32 |
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- name: counts_log |
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sequence: float32 |
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- name: counts_log_norm |
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sequence: float32 |
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- name: gene_names |
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sequence: string |
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- name: control_counts |
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sequence: float32 |
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- name: control_counts_norm |
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sequence: float32 |
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- name: control_counts_log |
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sequence: float32 |
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- name: control_counts_log_norm |
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sequence: float32 |
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- name: delta_counts |
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sequence: float32 |
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- name: delta_counts_norm |
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sequence: float32 |
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- name: delta_counts_log |
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sequence: float32 |
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- name: delta_counts_log_norm |
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sequence: float32 |
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- name: cell_line |
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dtype: string |
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- name: perturbation |
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dtype: string |
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- name: compound_concentration |
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dtype: float64 |
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- name: compound_unit |
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dtype: string |
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- name: compound_smiles |
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dtype: string |
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- name: mechanism |
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dtype: string |
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- name: moa |
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dtype: string |
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- name: biological_effect |
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dtype: string |
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- name: experimental_id |
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dtype: string |
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- name: timepoint |
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dtype: string |
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- name: text |
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dtype: string |
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- name: text_embeddings |
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sequence: float32 |
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- name: chembert_embeddings |
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sequence: float32 |
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splits: |
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- name: train |
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num_bytes: 176083286910 |
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num_examples: 49392 |
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download_size: 65016664023 |
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dataset_size: 176083286910 |
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--- |
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**I AM NOT AFFILIATED WITH NOVARTIS IN ANY WAY; THIS IS SIMPLY AN UPLOAD OF THEIR DATASET, "[NOVARTIS/DRUG-SEQ U2OS MOABOX DATASET](https://zenodo.org/records/14291446)."** |
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# Novartis DRUG-seq U2OS MoABox Dataset |
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This dataset profiles transcriptomic responses of the **U-2 OS** human osteosarcoma cell line to a broad collection of small molecule perturbations. It contains **49,392 observations** spanning **3,742 unique compounds** tested at **4 distinct dosages + `0.0`**, each annotated with their respective **mechanisms of action (MoA)**. |
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Each observation records gene expression data for **59,594 genes**. |
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The dataset was generated using the DRUG-seq platform, enabling high-throughput, unbiased transcriptomic readouts suited for drug discovery applications. |
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## Additional Information |
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- Perturbation dosages range across 4 unique concentration values + `0.0`. |
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- Observations include multiple experimental replicates and plate layouts. |
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- **Normalized counts** were scaled so that the total expression per cell sums to `1e4`. |
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- **Control counts** represent the average expression of each gene across all control cells. |
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- **Delta values** are computed as the difference between each sample's expression and the corresponding control mean. |
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- **SMILES** strings and **mechanism of action (MoA)** annotations curated by Novartis, retrieved from the [ChEMBL](https://www.ebi.ac.uk/chembl/) database and enhanced with additional sources. |
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## Citations |
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> Hadjikyriacou, A., Yang, C., Henault, M., *et al.* |
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> **Novartis DRUG-seq U2OS MoABox Dataset** |
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> [Novartis DRUG-seq GitHub Repository](https://github.com/Novartis/DRUG-seq) |
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> Hadjikyriacou, A., Yang, C., Henault, M., Ge, R., Mansur, L., Lindeman, A., Russ, C., Renner, S., Hild, M., Jenkins, J., Gubser-Keller, C., Li, J., Ho, D. J., Neri, M., Sigoillot, F. D., & Ihry, R. (2025). |
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> **Novartis/DRUG-seq U2OS MoABox Dataset (1.0.0) [Data set].** Zenodo. |
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> https://doi.org/10.5281/zenodo.14291446 |
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> Li, J., Ho, D. J., Henault, M., Yang, C., Neri, M., Ge, R., Renner, S., Mansur, L., Lindeman, A., Tumkaya, T., Russ, C., Hild, M., Gubser Keller, C., Jenkins, J. L., Worringer, K. A., Sigoillot, F. D., & Ihry, R. J. (2021). |
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> **DRUG-seq Provides Unbiased Biological Activity Readouts for Drug Discovery.** bioRxiv. |
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> https://doi.org/10.1101/2021.06.07.447456 |
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> [Full text PDF](https://www.biorxiv.org/content/early/2021/06/08/2021.06.07.447456.full.pdf) |
