genes listlengths 263 6.85k | expressions listlengths 263 6.85k | drug stringclasses 47
values | drugname_drugconc stringclasses 93
values | cell_line stringclasses 52
values | sample stringclasses 96
values | BARCODE_SUB_LIB_ID stringlengths 16 16 |
|---|---|---|---|---|---|---|
[
5,
6,
11,
19,
20,
32,
49,
58,
70,
78,
103,
107,
108,
114,
127,
128,
156,
164,
167,
202,
214,
221,
233,
234,
246,
252,
255,
262,
266,
270,
290,
294,
296,
297,
305,
307,
310,
312,
319,
333,
340,
347,
356,
375,
377,
378,
382,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
2,
1,
1,
1,
1,
6,
1,
1,
2,
2,
2... | 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,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
5,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
2,
1,
1,
1,
1,
1,
2,
3,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
1,
1,
2,
2,
2,
2,
1,
1,
1... | 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,
... | [
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | 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,
... | [
2,
3,
2,
1,
2,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
4,
1,
4,
1,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
4,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
3,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
4,
3... | 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,
... | [
1,
1,
1,
2,
1,
2,
1,
2,
1,
1,
2,
1,
2,
1,
2,
1,
1,
2,
1,
2,
1,
2,
1,
1,
2,
1,
1,
1,
1,
4,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1... | Cetuximab | [('Cetuximab', 0.068596, 'uM')] | CVCL_0332 | smp_804 | 01_01_26-lib_316 |
[
35,
45,
51,
77,
82,
86,
106,
128,
139,
156,
171,
202,
214,
226,
253,
266,
277,
289,
298,
307,
319,
326,
338,
359,
363,
368,
370,
396,
404,
428,
441,
459,
470,
472,
498,
508,
517,
553,
563,
604,
609,
626,
642,
650,
689,
706,
... | [
1,
1,
1,
2,
1,
1,
1,
2,
1,
1,
1,
1,
1,
3,
1,
1,
1,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
3,
1,
1,
1,
1,
1,
2,
1,
1,
2,
1,
1... | 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,... | [
1,
1,
1,
1,
3,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1,
2,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
3,
1,
2,
3,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
2,
5,
1,
1,
1,
1,
1,
1,
1,
1,
1,
5,
6... | 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,
... | [
1,
3,
1,
1,
1,
1,
1,
2,
1,
2,
2,
1,
1,
2,
2,
1,
1,
2,
1,
1,
1,
3,
1,
1,
1,
1,
1,
1,
1,
2,
1,
2,
4,
1,
1,
1,
1,
1,
1,
1,
1,
9,
1,
2,
1,
2,
1,
1,
1,
1,
1,
2,
1,
2,
2,
2,
2,
1,
4,
1,
1,
1,
1,
1... | 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,
... | [
1,
1,
1,
1,
1,
2,
3,
1,
1,
1,
3,
1,
1,
1,
2,
4,
1,
1,
2,
1,
1,
1,
1,
1,
2,
3,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
2,
2,
2,
1,
1,
2,
2,
1,
4,
1,
1,
1,
1,
1,
1,
4,
3,
1,
1,
1,
1,
1,
1,
1,
7,
1,
1... | 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,... | [
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
2,
1,
2,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
3,
2,
1,
2,
2,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1,
1,
2,
1,
1,
1,
1... | 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... | [
3,
5,
2,
1,
2,
1,
1,
1,
2,
1,
1,
1,
1,
5,
1,
1,
1,
2,
2,
1,
1,
3,
1,
2,
2,
1,
4,
2,
1,
1,
1,
1,
6,
1,
5,
5,
1,
1,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1,
1,
2,
1,
2,
1,
4,
2,
2,
4,
2,
2,
1,
3,
1,
6,
1... | Cetuximab | [('Cetuximab', 0.068596, 'uM')] | CVCL_0218 | smp_804 | 01_01_74-lib_316 |
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.
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 |
|
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
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
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. |
- Downloads last month
- 249


