README.md

metadata

license: cc-by-4.0
tags:
  - biology
dataset_info:
  features:
    - name: counts
      sequence: int32
    - name: counts_norm
      sequence: float32
    - name: counts_log
      sequence: float32
    - name: counts_log_norm
      sequence: float32
    - name: gene_names
      sequence: string
    - name: control_counts
      sequence: float32
    - name: control_counts_norm
      sequence: float32
    - name: control_counts_log
      sequence: float32
    - name: control_counts_log_norm
      sequence: float32
    - name: delta_counts
      sequence: float32
    - name: delta_counts_norm
      sequence: float32
    - name: delta_counts_log
      sequence: float32
    - name: delta_counts_log_norm
      sequence: float32
    - name: cell_line
      dtype: string
    - name: perturbation
      dtype: string
    - name: compound_concentration
      dtype: float64
    - name: compound_unit
      dtype: string
    - name: compound_smiles
      dtype: string
    - name: mechanism
      dtype: string
    - name: moa
      dtype: string
    - name: biological_effect
      dtype: string
    - name: experimental_id
      dtype: string
    - name: timepoint
      dtype: string
    - name: text
      dtype: string
    - name: text_embeddings
      sequence: float32
    - name: chembert_embeddings
      sequence: float32
  splits:
    - name: train
      num_bytes: 84911752257
      num_examples: 24262
  download_size: 12664654443
  dataset_size: 84911752257
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

Dataset Description

A549 Chemical Perturbation Dataset (SciPlex2)

This dataset captures transcriptional responses of A549, a human lung adenocarcinoma cell line, to drug perturbations. Cells were treated with one of four small molecules:

• Dexamethasone, corticosteroid receptor agonist
• Nutlin-3a, p53-MDM2 interaction antagonist
• BMS-345541, inhibitor of NF-κB–dependent transcription
• Vorinostat (SAHA), histone deacetylase (HDAC) inhibitor

Each compound was applied for 24 hours across seven doses, in triplicate, resulting in 84 compound–dose–replicate conditions, along with additional vehicle controls. Single-cell transcriptional profiles were generated using sci-RNA-seq.

Additional Information

• Normalized counts were scaled so that the total expression per cell sums to 1e4.
• Control counts represent the average expression of each gene across all control cells.
• Delta values are computed as the difference between each sample's expression and the corresponding control mean.
• SMILES strings and mechanism of action (MoA) annotations were retrieved from the ChEMBL database and enhanced with additional sources.

Citation

Srivatsan, S. R., McFaline-Figueroa, J. L., Ramani, V. et al.
Massively multiplex chemical transcriptomics at single-cell resolution
Science, 367, 45–51 (2020).
https://doi.org/10.1126/science.aax6234