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genes
listlengths
263
6.85k
expressions
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263
6.85k
drug
stringclasses
47 values
drugname_drugconc
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93 values
cell_line
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sample
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96 values
BARCODE_SUB_LIB_ID
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16
16
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_1055
smp_804
01_01_05-lib_316
[ 11, 26, 42, 78, 82, 106, 138, 157, 167, 220, 224, 257, 266, 275, 290, 321, 363, 383, 414, 415, 444, 455, 495, 496, 553, 575, 577, 587, 650, 652, 668, 670, 700, 726, 728, 730, 736, 790, 803, 812, 813, 826, 849, 872, 885, 910, ...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_0459
smp_804
01_01_08-lib_316
[ 15, 16, 19, 20, 31, 32, 42, 45, 48, 54, 69, 77, 78, 103, 108, 112, 131, 137, 138, 140, 146, 156, 160, 195, 210, 214, 216, 229, 232, 233, 235, 236, 244, 246, 259, 266, 294, 297, 298, 307, 313, 337, 354, 358, 402, 407, 413, ...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_1478
smp_804
01_01_23-lib_316
[ 5, 19, 51, 59, 84, 128, 137, 138, 158, 205, 214, 221, 231, 234, 235, 270, 290, 292, 298, 345, 382, 440, 459, 461, 472, 475, 478, 483, 485, 500, 509, 515, 521, 541, 549, 553, 555, 569, 605, 617, 620, 623, 634, 642, 643, 650, ...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_0480
smp_804
01_01_24-lib_316
[ 5, 12, 77, 95, 103, 108, 128, 156, 167, 187, 223, 233, 235, 244, 246, 293, 298, 325, 326, 350, 353, 375, 378, 403, 404, 418, 429, 430, 436, 455, 483, 513, 515, 517, 541, 561, 563, 569, 575, 601, 605, 609, 623, 638, 643, 649, ...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_0332
smp_804
01_01_26-lib_316
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_1098
smp_804
01_01_45-lib_316
[ 5, 11, 20, 21, 43, 68, 77, 82, 95, 106, 109, 113, 114, 124, 131, 139, 141, 146, 155, 156, 157, 158, 163, 174, 192, 200, 202, 205, 211, 214, 231, 233, 234, 235, 244, 247, 252, 274, 275, 277, 278, 280, 291, 294, 335, 344, 345,...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_0480
smp_804
01_01_52-lib_316
[ 10, 11, 38, 50, 54, 55, 56, 68, 70, 78, 79, 103, 107, 108, 113, 114, 124, 128, 134, 138, 139, 149, 187, 202, 211, 220, 232, 234, 246, 247, 253, 255, 275, 279, 283, 292, 293, 299, 310, 316, 326, 344, 347, 348, 363, 379, 403, ...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_1724
smp_804
01_01_59-lib_316
[ 16, 19, 21, 26, 32, 38, 56, 59, 69, 70, 77, 81, 88, 103, 106, 108, 112, 113, 128, 137, 138, 139, 141, 148, 156, 163, 171, 174, 189, 195, 197, 206, 220, 223, 224, 226, 232, 234, 235, 244, 246, 252, 253, 266, 267, 275, 284, ...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_0320
smp_804
01_01_61-lib_316
[ 3, 19, 21, 26, 31, 32, 45, 51, 54, 56, 59, 68, 70, 78, 86, 95, 108, 124, 128, 132, 137, 138, 139, 140, 144, 147, 148, 149, 154, 156, 200, 202, 214, 233, 234, 235, 236, 244, 246, 273, 274, 284, 291, 292, 298, 302, 312, 316,...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_0546
smp_804
01_01_66-lib_316
[ 11, 19, 21, 24, 25, 27, 31, 32, 42, 43, 48, 50, 52, 56, 58, 59, 63, 68, 69, 70, 76, 77, 78, 103, 106, 107, 108, 109, 113, 114, 117, 121, 128, 134, 137, 138, 140, 144, 147, 149, 153, 154, 156, 158, 163, 171, 174, 195, 200...
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Cetuximab
[('Cetuximab', 0.068596, 'uM')]
CVCL_0218
smp_804
01_01_74-lib_316
End of preview. Expand in Data Studio

Emerald Bay

Emerald Bay is a single-cell perturbation dataset of over 1.8M transcriptomic profiles spanning 52 cell lines and 91 drug treatments, including combinations. Generated using Tahoe Therapeutics's MOSAIC high-throughput platform, it comprises a curated set of anticancer agents applied at multiple doses across a MOSAIC tumor pool optimized for five-day culture. The dataset provides two readouts: a transcriptional profile at single-cell resolution and a drug-phenotype measure derived from cell-count proportions at the five-day endpoint.

img

Quickstart

from datasets import load_dataset
# Load dataset in streaming mode
ds = load_dataset("tahoebio/EmeraldBay", streaming=True, split="train")
# View the first record
next(ds.iter(1))

Setting streaming=True instantiates an IterableDataset and prevents needing to download the full dataset first.

Tutorials

Please refer to our tutorials for examples on using the data, accessing metadata tables and converting to/from the anndata format.

Please see the Data Loading Tutorial for a walkthrough on using the data.

Notebook URL Colab
Loading the dataset from huggingface, accessing metadata, mapping to anndata Link Open in Colab

Dataset Features

We provide multiple tables with the dataset including the main data (raw counts) in the expression_data table as well as various metadata in the gene_metadata,sample_metadata,drug_metadata,cell_line_metadata, and summary_statistics tables.

The main data can be downloaded as follows:

expression_data = load_dataset("tahoebio/EmeraldBay", "expression_data", split="train")

Per-cell transcriptomic profiles are provided (1,831,648 cells across 116 shards), with each row corresponding to one cell.

The expression_data table has the following fields:

Field Type Description
genes sequence<int64> Gene token IDs for genes with non-zero expression in the cell. Aligned with expressions. Map to gene_symbol/ensembl_id via gene_metadata.
expressions sequence<float64> Raw count values, aligned with genes.
drug string Name of the treatment. DMSO_TF marks vehicle controls.
drugname_drugconc string Compound × concentration string (e.g. "[('Cetuximab', 0.068596, 'uM')]"), matching the condition key in summary_statistics.
cell_line string Cellosaurus ID of the cancer cell line (e.g. CVCL_1055).
sample string Unique sample identifier (distinguishes replicate treatments).
BARCODE_SUB_LIB_ID string Combination of barcode and sublibrary identifiers. Unique per cell.

Additional metadata

Gene Metadata

gene_metadata = load_dataset("tahoebio/EmeraldBay", "gene_metadata", split="train")

The gene_metadata table maps each gene to its integer token ID used in the expression data. It extends the Tahoe-100M gene vocabulary: the first 62,710 rows preserve the Tahoe-100M token IDs verbatim, and 574 additional genes present in EmeraldBay but not Tahoe-100M are appended at the end of the vocabulary.

Column Name Description
gene_symbol The HGNC-approved gene symbol corresponding to each gene (e.g., TP53, BRCA1).
ensembl_id The Ensembl gene identifier (e.g., ENSG00000000003) based on Ensembl release 109 and genome build 38.
token_id An integer token ID used to represent each gene. This is the ID used in the genes field in the main data.

Cell Line Metadata

img

cell_line_metadata = load_dataset("tahoebio/EmeraldBay", "cell_line_metadata", split="train")

Driver-mutation annotations for the 52 EmeraldBay cell lines. This is a subset of the Tahoe-100M cell_line_metadata table filtered to the EmeraldBay cell-line panel; the schema is preserved verbatim. The table has multiple rows per cell line (one per curated driver mutation; 1–51 rows per line, mean ~9). Join on Cell_ID_Cellosaur to match the cell_line field in expression_data and summary_statistics.

Column Name Description
cell_name Standard name of the cancer cell line (e.g., A549).
Cell_ID_DepMap Unique identifier for the cell line in the DepMap project (e.g., ACH-000681).
Cell_ID_Cellosaur Cellosaurus accession ID (e.g., CVCL_0023). Join key against cell_line in expression_data and summary_statistics.
Organ Tissue or organ of origin for the cell line (e.g., Lung).
Driver_Gene_Symbol HGNC-approved symbol of a known or putative driver gene with functional alterations in this cell line (e.g., KRAS, CDKN2A).
Driver_VarZyg Zygosity of the driver variant (e.g., Hom for homozygous, Het for heterozygous).
Driver_VarType Type of genetic alteration (e.g., Missense, Frameshift, Stopgain, Deletion).
Driver_ProtEffect_or_CdnaEffect Specific protein or cDNA-level annotation of the mutation (e.g., p.G12S, p.Q37).
Driver_Mech_InferDM Inferred functional mechanism of the mutation (e.g., LoF for loss-of-function, GoF for gain-of-function).
Driver_GeneType_DM Classification of the driver gene as an Oncogene or Suppressor.

Drug Metadata

drug_metadata = load_dataset("tahoebio/EmeraldBay", "drug_metadata", split="train")

One row per single-drug perturbation in EmeraldBay (27 drugs; DMSO controls are excluded per the Tahoe-100M convention). Curated with Claude and validated against MedChemExpress, ClinicalTrials.gov, and PubChem. Drug-combination conditions (e.g. Adagrasib+Cetuximab) are not represented as rows here; join expression_data.drug against this table for single-drug perturbations and parse drugname_drugconc for combination treatments.

Column Name Description
drug Name of the treatment. Unique key for this table.
targets Known molecular targets of the compound (gene symbol(s)).
mutations Specific target mutation(s) the compound is selective for, when applicable (e.g. KRASG12C).
moa-broad Broad classification of the compound's mechanism of action (typically "inhibitor/antagonist", "activator/agonist", or "unclear").
moa-fine Specific functional MoA annotation (e.g. "RAS inhibitor", "MEK inhibitor", "Proteasome inhibitor").
human-use "yes"/"no" — whether the compound is approved for human use.
clinical-trials "yes"/"no" — whether the compound has been evaluated in any registered clinical trials.
claude-notes-approval Contextual notes on the compound's approval status / clinical usage, generated by Claude.
pubchem-cid PubChem Compound Identifier.
canonical-smiles Canonical SMILES string representing the molecular structure (null for antibody drugs).

Sensitivity Readout

img

summary_statistics = load_dataset("tahoebio/EmeraldBay", "summary_statistics", split="train")

Per-(cell line, condition) growth-rate summary statistics: 4,992 rows covering 52 cancer cell lines × 93 conditions (single-drug, drug-combination, and DMSO_T0 time-zero controls). This is the raw summary table; downstream loaders typically drop DMSO_T0, exclude multi-drug conditions, and mean-aggregate replicates per (cell line, condition).

Column Name Description
cell_line Cellosaurus ID of the cancer cell line (e.g., CVCL_0023).
condition Compound × concentration, e.g. [('Encorafenib', 0.1, 'uM')]. May contain multiple tuples for combination treatments, and DMSO_T0 marks time-zero vehicle controls.
growth_rate Scalar growth-rate response of the cell line to the treatment.
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