donor_id stringlengths 8 63 | embedding listlengths 512 512 | disease_label stringclasses 17 values | dataset_id stringclasses 40 values |
|---|---|---|---|
1000_1001_3faad104-2ab8-4434-816d-474d8d2641db | [
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... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1001_1002_3faad104-2ab8-4434-816d-474d8d2641db | [
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... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1002_1003_3faad104-2ab8-4434-816d-474d8d2641db | [
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1003_1004_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.06837392598390579... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1004_1005_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.069317974150180... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1004_218acb0f-9f2f-4f76-b90b-15a4b7c7f629 | [
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0.37743040919303894,
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-0.8594089150428... | systemic lupus erythematosus | 218acb0f-9f2f-4f76-b90b-15a4b7c7f629 |
1005_1006_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.07447472214698792,... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1006_1007_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.06386562436819077,... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1007_1008_3faad104-2ab8-4434-816d-474d8d2641db | [
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... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1008_1009_3faad104-2ab8-4434-816d-474d8d2641db | [
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... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1009_1010_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.20161080360412598,
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0.0615005530416965... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1010_1011_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.200028657913208,
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0.0708637684583664,
... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1011_1012_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.14043019711971283,
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... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1012_1013_3faad104-2ab8-4434-816d-474d8d2641db | [
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-0... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1014_1015_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.06898243725299835,
... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1014_218acb0f-9f2f-4f76-b90b-15a4b7c7f629 | [
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-0.773257076740264... | systemic lupus erythematosus | 218acb0f-9f2f-4f76-b90b-15a4b7c7f629 |
1015_1016_3faad104-2ab8-4434-816d-474d8d2641db | [
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0.07056688517332077,
... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
1015_218acb0f-9f2f-4f76-b90b-15a4b7c7f629 | [
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... | systemic lupus erythematosus | 218acb0f-9f2f-4f76-b90b-15a4b7c7f629 |
1016_1017_3faad104-2ab8-4434-816d-474d8d2641db | [
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-... | normal | 3faad104-2ab8-4434-816d-474d8d2641db |
End of preview. Expand
in Data Studio
Dataset Card for DONORxEMBED-aligned
This dataset contains pre-computed PULSAR donor embeddings for 2,804 peripheral blood mononuclear cell (PBMC) samples from 41 independent studies, totaling over 10 million cells with paired diagnostic annotations. The embeddings are generated using PULSAR (Patient Understanding Leveraging Single-cell universAl Representation), a multi-scale, multi-cellular foundation model designed to transform PBMC scRNA-seq samples into unified donor representations.
This dataset hosts the disease-aligned model (PULSAR-aligned) embeddings. A zero-shot variant is also available (see https://huggingface.co/datasets/KuanP/PULSAR_DONORxEMBED_zero_shot).
Dataset Details
Uses
Direct Use
This dataset is intended for:
- Disease classification through reference-based mapping using k-nearest neighbor search in the embedding space
- Building searchable vector databases for flexible, scalable disease classification
- Benchmarking machine learning models for immune-related disease prediction
- Cross-cohort generalization studies in immunology
- Population-level analysis of immune variation across diseases
Dataset Structure
The dataset contains 2,804 samples with the following fields:
- donor_id (string): Unique identifier for each donor/sample
- embedding (sequence of float32): 512-dimensional PULSAR donor embedding vector
- disease_label (string): Disease annotation following Mondo Disease Ontology standards
- dataset_id (string): Source dataset identifier
Dataset Creation
Curation Rationale
This dataset was created to enable reference-based disease classification and to demonstrate PULSAR's capacity to capture disease-relevant donor-level signatures. The comprehensive reference cohort allows for scalable disease classification through vector database search, enabling continuous expansion without model re-training.
Source Data
The dataset was assembled from 41 sources:
- 32 datasets from CZ CELLxGENE Census database
- 1 dataset from Single Cell Portal (SCP)
- 8 additional curated sources
Citation
BibTeX:
[More Information Needed]
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