Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Could not read the parquet files: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
Error code: FileSystemError
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
chrom large_string | pos large_string | ref large_string | alt large_string | rsid large_string | embedding large list |
|---|---|---|---|---|---|
1 | 10001 | T | TC | nan | [
-0.045623779296875,
0.01313018798828125,
-0.0066070556640625,
-0.055908203125,
0.013580322265625,
0.0268707275390625,
-0.038787841796875,
-0.0288543701171875,
0.019561767578125,
0.05279541015625,
-0.006450653076171875,
-0.06939697265625,
0.0982666015625,
-0.00746917724609375,
-0.03097534... |
1 | 10001 | T | A | rs1570391677 | [
-0.0384521484375,
-0.0007123947143554688,
-0.005649566650390625,
-0.03448486328125,
0.0261993408203125,
0.0408935546875,
-0.06719970703125,
0.0173187255859375,
-0.0302581787109375,
0.043487548828125,
0.02313232421875,
-0.042755126953125,
0.1014404296875,
-0.002994537353515625,
-0.0343933... |
1 | 10001 | T | C | rs1570391677 | [
-0.03887939453125,
0.001293182373046875,
-0.0045623779296875,
-0.0291595458984375,
0.02069091796875,
0.040130615234375,
-0.068359375,
-0.01380157470703125,
-0.0265960693359375,
0.07342529296875,
0.032501220703125,
-0.0596923828125,
0.10906982421875,
-0.0022792816162109375,
-0.03424072265... |
1 | 10001 | T | G | nan | [
-0.05499267578125,
-0.0019407272338867188,
-0.006549835205078125,
-0.04937744140625,
0.021575927734375,
0.0231781005859375,
-0.04901123046875,
-0.004276275634765625,
0.0237884521484375,
0.03619384765625,
0.0008406639099121094,
-0.059814453125,
0.09649658203125,
-0.007335662841796875,
-0.... |
1 | 10002 | A | G | nan | [
-0.048248291015625,
-0.006572723388671875,
-0.00681304931640625,
-0.0589599609375,
0.0232696533203125,
0.020721435546875,
-0.03717041015625,
0.00862884521484375,
0.056182861328125,
0.004924774169921875,
-0.0174102783203125,
-0.0657958984375,
0.0845947265625,
-0.007785797119140625,
-0.040... |
1 | 10002 | A | C | rs1570391692 | [
-0.0169830322265625,
-0.0022735595703125,
-0.0062713623046875,
-0.042572021484375,
0.0290374755859375,
0.035369873046875,
-0.058746337890625,
-0.01910400390625,
0.024139404296875,
0.042510986328125,
0.023590087890625,
-0.0408935546875,
0.11309814453125,
-0.003391265869140625,
-0.03436279... |
1 | 10002 | A | T | nan | [
-0.052703857421875,
-0.0047454833984375,
-0.0069427490234375,
-0.0673828125,
0.01540374755859375,
0.0193023681640625,
-0.0343017578125,
-0.00679779052734375,
0.040069580078125,
0.0154571533203125,
-0.0245513916015625,
-0.061859130859375,
0.08355712890625,
-0.008056640625,
-0.034515380859... |
1 | 10003 | A | T | nan | [
-0.055877685546875,
0.01065826416015625,
-0.00611114501953125,
-0.0643310546875,
0.0247955322265625,
0.0242767333984375,
-0.040130615234375,
-0.001800537109375,
0.0297088623046875,
0.017547607421875,
-0.018707275390625,
-0.06219482421875,
0.0859375,
-0.00740814208984375,
-0.0335388183593... |
1 | 10003 | A | G | nan | [
-0.05078125,
0.009918212890625,
-0.005855560302734375,
-0.0560302734375,
0.0308837890625,
0.02581787109375,
-0.04296875,
0.0128173828125,
0.045654296875,
0.00719451904296875,
-0.011932373046875,
-0.0657958984375,
0.08880615234375,
-0.007106781005859375,
-0.040557861328125,
0.0474548339... |
1 | 10003 | A | C | rs1570391694 | [
-0.02081298828125,
0.02716064453125,
-0.00460052490234375,
-0.03802490234375,
0.019744873046875,
0.039520263671875,
-0.050567626953125,
-0.0080108642578125,
-0.0003402233123779297,
0.043212890625,
0.034271240234375,
-0.034576416015625,
0.120361328125,
-0.0021648406982421875,
-0.036254882... |
End of preview.
Variant Foundation Embeddings
Here we present the variant level embeddings for large-scale genetic analyis as described in 'Incorporating LLM Embeddings for Variation Across the Human Genome,' based on curated annotations using high quality functional data from FAVOR, ClinVar, and GWAS Catalog. We currently present embeddings using either OpenAI's text-embedding-3-large (3072-dimensional) or Qwen's Qwen3-Embedding-0.6B (1024-dimensional) models.
Genetic variants are identified with their chromosome, position (hg38 build), reference allele based on UKB coding, alternate allele based on UKB coding, and their respective LLM embeddings.
Currently we release datasets at the following scales:
- HapMap3 & MEGA (~1.5 million variants, OpenAI GPT-3.5)
- UKB Imputed (~90 million variants, OpenAI GPT-3.5)
- All FAVOR Variants (~9 billion variants, Qwen3-0.6B)
Updates
02-07-26
We have fixed an issue with the chromosome 3 embeddings in the UKB imputed set at /UKB-Imputed-90m/chr03/.
Dataset Schema (OpenAI text-embedding-3-large)
| Field | Type | Description |
|---|---|---|
chrom |
string | Chromosome (e.g., "1", "X") |
pos |
string | Base-pair position (hg38 coordinate system) |
ref_UKB |
string | Reference allele (A, C, G, T) |
alt_UKB |
string | Alternate allele (A, C, G, T) |
embedding |
list[float] | Embedding vector (dimension 3072, float) |
Dataset Schema (Qwen qwen3-embedding-0.6B)
| Field | Type | Description |
|---|---|---|
chrom |
string | Chromosome (e.g., "1", "X") |
pos |
string | Base-pair position (hg38 coordinate system) |
ref_UKB |
string | Reference allele (A, C, G, T) |
alt_UKB |
string | Alternate allele (A, C, G, T) |
embedding |
list[float] | Embedding vector (dimension 1024, float) |
- Downloads last month
- 8,356