Dataset Viewer
Auto-converted to Parquet Duplicate
chrom
string
start
uint32
end
uint32
allele_string
string
protein_variant
string
am_class
string
am_pathogenicity
float32
tier
int8
1
69,428
69,428
T/G
F113C
likely_benign
0.2138
0
1
69,761
69,761
A/T
D224V
likely_benign
0.1062
0
1
69,850
69,850
C/A
P254T
likely_benign
0.2463
0
1
69,896
69,896
C/A
S269Y
likely_benign
0.2397
0
1
69,898
69,898
G/A
V270M
likely_benign
0.1642
0
1
930,204
930,204
G/A
R41Q
likely_benign
0.0866
0
1
930,315
930,315
A/G
H78R
likely_benign
0.0746
0
1
939,284
939,284
T/G
L177R
likely_benign
0.1098
0
1
939,398
939,398
G/A
G215D
ambiguous
0.3538
0
1
942,933
942,933
G/A
G480E
likely_benign
0.1109
0
1
942,935
942,935
T/G
C481G
likely_benign
0.0461
0
1
942,944
942,944
C/T
P484S
likely_benign
0.0717
0
1
942,951
942,951
C/T
P486L
likely_benign
0.0714
0
1
943,936
943,936
A/C
Y610S
ambiguous
0.3808
0
1
943,938
943,938
G/A
V611M
likely_benign
0.0774
0
1
944,100
944,100
G/A
G665R
likely_benign
0.2684
0
1
952,420
952,420
G/A
R395C
likely_benign
0.1281
0
1
952,422
952,422
G/T
T394N
likely_benign
0.1299
0
1
953,278
953,278
A/C
I300S
likely_benign
0.1082
0
1
953,859
953,859
C/A
A271S
likely_benign
0.0998
0
1
961,944
961,944
C/T
A203V
likely_benign
0.2947
0
1
961,946
961,946
C/T
H204Y
likely_pathogenic
0.8024
0
1
962,359
962,359
T/C
L239P
likely_pathogenic
0.9549
0
1
965,048
965,048
A/G
K596E
likely_pathogenic
0.9395
0
1
966,544
966,544
C/G
H5D
likely_benign
0.2335
0
1
966,748
966,748
C/T
A43V
likely_benign
0.101
0
1
972,420
972,420
C/T
S333L
likely_benign
0.0536
0
1
972,895
972,895
G/A
G346D
likely_benign
0.079
0
1
972,942
972,942
C/T
R362C
likely_benign
0.0744
0
1
973,842
973,842
G/A
A482T
likely_benign
0.0927
0
1
973,857
973,857
C/T
R487C
likely_benign
0.0963
0
1
973,929
973,929
T/C
S511P
likely_benign
0.0621
0
1
973,930
973,930
C/T
S511F
likely_benign
0.1126
0
1
978,946
978,946
G/A
A695V
likely_benign
0.0897
0
1
978,953
978,953
C/G
E693Q
likely_benign
0.0669
0
1
979,229
979,229
C/T
A601T
likely_benign
0.0968
0
1
979,231
979,231
G/A
A600V
likely_benign
0.1069
0
1
979,459
979,459
C/T
R524Q
likely_benign
0.0844
0
1
979,495
979,495
C/A
S512I
likely_benign
0.1142
0
1
979,559
979,559
G/A
P491S
likely_benign
0.0805
0
1
980,020
980,020
G/A
P337L
likely_benign
0.086
0
1
980,162
980,162
C/T
D290N
likely_benign
0.1213
0
1
980,780
980,780
G/T
P84T
likely_benign
0.0884
0
1
1,014,275
1,014,275
C/T
R99W
likely_benign
0.1158
0
1
1,071,822
1,071,822
T/C
N249D
likely_benign
0.0745
0
1
1,071,843
1,071,843
G/A
P242S
likely_benign
0.0603
0
1
1,091,533
1,091,533
C/T
R4Q
likely_benign
0.1621
0
1
1,091,534
1,091,534
G/A
R4W
likely_benign
0.2639
0
1
1,179,288
1,179,288
G/A
G25S
likely_benign
0.1188
0
1
1,180,036
1,180,036
C/T
P68S
likely_benign
0.0922
0
1
1,180,081
1,180,081
C/T
R83W
likely_benign
0.0781
0
1
1,180,082
1,180,082
G/A
R83Q
likely_benign
0.0744
0
1
1,180,122
1,180,122
C/G
H96Q
likely_benign
0.1044
0
1
1,180,123
1,180,123
T/C
C97R
likely_benign
0.072
0
1
1,180,124
1,180,124
G/C
C97S
likely_benign
0.0854
0
1
1,180,168
1,180,168
G/A
G112R
likely_benign
0.1159
0
1
1,180,223
1,180,223
C/A
A130D
likely_benign
0.1044
0
1
1,184,998
1,184,998
G/A
M430I
likely_benign
0.2402
0
1
1,185,108
1,185,108
A/C
K467T
likely_benign
0.0448
0
1
1,197,558
1,197,558
G/A
G578D
likely_benign
0.106
0
1
1,197,585
1,197,585
C/A
P587H
likely_benign
0.0847
0
1
1,197,696
1,197,696
C/T
P624L
likely_benign
0.0629
0
1
1,204,118
1,204,118
C/T
V173M
likely_benign
0.1018
0
1
1,204,184
1,204,184
C/T
A151T
likely_benign
0.1299
0
1
1,204,186
1,204,186
T/C
N150S
likely_benign
0.2731
0
1
1,204,481
1,204,481
A/T
F106I
likely_benign
0.3002
0
1
1,228,583
1,228,583
C/T
G71R
likely_pathogenic
0.9328
0
1
1,228,651
1,228,651
A/G
V48A
likely_benign
0.0529
0
1
1,228,693
1,228,693
G/A
A34V
likely_benign
0.0709
0
1
1,228,711
1,228,711
G/A
A28V
likely_benign
0.0703
0
1
1,232,799
1,232,799
A/G
E174G
likely_benign
0.0841
0
1
1,232,800
1,232,800
G/C
E174D
likely_benign
0.0457
0
1
1,232,801
1,232,801
C/G
P175A
likely_benign
0.091
0
1
1,242,863
1,242,863
A/C
L261R
likely_benign
0.2846
0
1
1,242,885
1,242,885
T/A
S254C
likely_benign
0.2247
0
1
1,243,102
1,243,102
A/G
C231R
likely_benign
0.0254
0
1
1,243,545
1,243,545
G/A
A180V
likely_benign
0.1008
0
1
1,243,546
1,243,546
C/T
A180T
likely_benign
0.0767
0
1
1,244,004
1,244,004
G/A
P161S
likely_benign
0.1037
0
1
1,244,419
1,244,419
C/T
A86T
likely_benign
0.0711
0
1
1,255,304
1,255,304
C/T
G227R
likely_pathogenic
0.6437
0
1
1,281,469
1,281,469
C/T
P46S
likely_benign
0.0692
0
1
1,284,003
1,284,003
A/C
Q126P
likely_benign
0.0689
0
1
1,285,573
1,285,573
C/T
S156L
likely_benign
0.0875
0
1
1,285,575
1,285,575
C/T
P157S
likely_benign
0.0751
0
1
1,285,621
1,285,621
A/G
Q172R
likely_benign
0.0788
0
1
1,287,218
1,287,218
C/T
A410V
likely_benign
0.0823
0
1
1,287,578
1,287,578
C/T
R461C
likely_benign
0.2856
0
1
1,287,579
1,287,579
G/A
R461H
likely_benign
0.0804
0
1
1,287,584
1,287,584
G/A
G463S
likely_benign
0.1895
0
1
1,290,684
1,290,684
C/G
A636G
likely_benign
0.1192
0
1
1,290,911
1,290,911
C/T
T645M
likely_benign
0.088
0
1
1,290,913
1,290,913
C/A
L646I
likely_benign
0.1369
0
1
1,291,133
1,291,133
T/A
V682E
likely_benign
0.2582
0
1
1,291,309
1,291,309
C/G
S703C
likely_pathogenic
0.5745
0
1
1,291,311
1,291,311
G/A
V704I
likely_benign
0.1744
0
1
1,291,377
1,291,377
G/A
G726S
likely_benign
0.1361
0
1
1,291,378
1,291,378
G/A
G726D
ambiguous
0.4252
0
1
1,291,470
1,291,470
C/A
P757T
likely_benign
0.0521
0
1
1,291,509
1,291,509
G/A
G770R
likely_benign
0.0917
0
End of preview. Expand in Data Studio

vepyr plugin cache — AlphaMissense (GRCh38, VEP 116)

A prebuilt, frequency-tiered Parquet cache of AlphaMissense pathogenicity predictions for use with vepyr, the Rust/DataFusion VEP-compatible variant annotation engine. It reproduces the CSQ output of Ensembl VEP 116's --plugin AlphaMissense without requiring the upstream TSV or the Perl plugin at annotation time.

Source version

This is the fact you most likely came here for.

Source file AlphaMissense_hg38.tsv.gz (canonical transcripts)
Source URL https://storage.googleapis.com/dm_alphamissense/AlphaMissense_hg38.tsv.gz
Upstream release DeepMind AlphaMissense, 2023 release (Cheng et al., Science 2023)
Source MD5 9fd167735f16a1b87da6eb3e4c25fcb5 (upstream gzip, from GCS object metadata)
Build input MD5 46d0028375cf95088bd014ff6855cffd (AlphaMissense_hg38.bgz.tsv.gz, the BGZF+tabix re-compression of the upstream file that was actually built from — declared as path_md5 in the manifest)
Source retrieved 2026-07-06
Genome build GRCh38 / hg38, 1-based, chr-prefixed contigs in source
Cache built 2026-09-05
Target VEP version Ensembl VEP 116 (VEP_plugins release/116 AlphaMissense.pm)
Build manifest plugins/alphamissense/alphamissense.source.toml
vepyr-plugins tag v0.1.1 — recorded in manifest.json as cache_source_version: v0.1.1@3e1c039
Source verification the BGZF re-compression used as build input was hashed (verified_md5 in manifest.json, differs from the upstream md5 by design, see the plugin README in vepyr-plugins)

AlphaMissense's distribution carries no internal version string — the file header is only the DeepMind copyright/licence banner — so the retrieval date above is the precise provenance marker for this build.

Provenance

Rebuilt on 2026-09-05 from sources verified against the v0.1.1 manifest; shard bytes are reproducible (a second build yields identical MD5s) since the tier stage orders rows totally. The sources block in manifest.json records url, declared and verified MD5, size and index digest for each input.

Contents

chr1.parquet … chr22.parquet, chrX/chrY/chrMT.parquet  25 per-contig shards
manifest.json                   schema, CSQ field mapping, per-shard row/tier counts, source provenance

Covers chr1–chr22, chrX, chrY and chrMT. Total ≈ 567 MB, 71,111,240 rows (84,844 warm / 71,026,396 cold).

Schema

column type role
chrom string contig
start uint32 1-based position
end uint32 1-based position
allele_string string REF/ALT, VEP-minimised
protein_variant string per-transcript match discriminator, {ref_aa}{Protein_position}{alt_aa}
am_class string → CSQ field am_class
am_pathogenicity float → CSQ field am_pathogenicity
tier int8 frequency tier — 0 = warm, 1 = cold

Emitted CSQ fields, in VEP's own order: am_class, am_pathogenicity.

am_class thresholds are AlphaMissense's own: likely benign if score < 0.34, *likely pathogenic* if score > 0.564, ambiguous otherwise.

Matching semantics

AlphaMissense is a per-transcript annotation: VEP matches each transcript consequence's amino-acid change against the row's protein_variant. The lookup key is therefore (chrom, start, end, allele_string) plus the protein_variant discriminator, which vepyr builds at runtime from the engine attributes ref_aa, Protein_position and alt_aa.

Alleles are stored minimised (allele_match = "minimised"), matching AlphaMissense.pm, which calls get_matched_variant_alleles() before comparing rows.

Frequency tiering

Each shard is sorted by (tier, start). A row's tier is inherited row-for-row from the release-116 GRCh38 variation cache this plugin cache was built against: a plugin row takes the tier of its matching variation row, and a plugin row with no match there is cold. tier = 0 is warm — 83,141 rows, 0.12% of the cache; tier = 1 is cold. Because warm rows are physically contiguous at the front of the file, a warm-only probe touches a handful of row groups instead of scanning the shard. Per-shard warm/cold counts are in manifest.json.

Quality profile

Generated 2026-09-05 by profile_plugin_cache.py (vepyr 0.4.0, Polars 1.39.3) from the shards in this commit; machine-readable copy in qa_profile.json.

Invariants

check status detail
schema ✅ pass 25 shards match the manifest
contig ✅ pass 0 foreign-contig rows in 25 shards
order ✅ pass 0 descending steps in 25 shards
tier_domain ✅ pass 0 rows with tier outside {0,1} in 25 shards
manifest_counts ✅ pass rows/warm/cold match in 25 shards
manifest_files ✅ pass 25 manifest contigs, no stray shards
positions ✅ pass 0 rows with start < 1 or end < start - 1 in 25 shards
allele_form ✅ pass 0 malformed allele strings in 25 shards
duplicates ✅ pass 0 duplicate probe keys in 25 shards (manifest assume_unique=false)

Contigs

contig rows warm cold warm % size
chr1 7,151,767 9,026 7,142,741 0.1% 57 MB
chr10 2,800,650 3,255 2,797,395 0.1% 22 MB
chr11 4,245,583 5,796 4,239,787 0.1% 34 MB
chr12 3,605,531 3,926 3,601,605 0.1% 29 MB
chr13 1,261,913 1,123 1,260,790 0.1% 10 MB
chr14 2,280,519 2,913 2,277,606 0.1% 18 MB
chr15 2,511,746 2,950 2,508,796 0.1% 20 MB
chr16 2,964,035 3,633 2,960,402 0.1% 24 MB
chr17 4,101,178 4,688 4,096,490 0.1% 33 MB
chr18 1,130,325 1,348 1,128,977 0.1% 9.0 MB
chr19 4,626,365 7,049 4,619,316 0.2% 37 MB
chr2 5,274,879 5,424 5,269,455 0.1% 42 MB
chr20 1,694,533 2,099 1,692,434 0.1% 13 MB
chr21 698,535 1,059 697,476 0.2% 5.6 MB
chr22 1,466,988 2,086 1,464,902 0.1% 12 MB
chr3 4,058,299 3,905 4,054,394 0.1% 32 MB
chr4 2,834,254 3,118 2,831,136 0.1% 23 MB
chr5 3,337,872 3,435 3,334,437 0.1% 27 MB
chr6 3,532,055 4,492 3,527,563 0.1% 28 MB
chr7 3,380,254 5,359 3,374,895 0.2% 27 MB
chr8 2,399,876 2,939 2,396,937 0.1% 19 MB
chr9 2,884,038 3,518 2,880,520 0.1% 23 MB
chrMT 24,074 0 24,074 0.0% 200 KB
chrX 2,670,963 1,694 2,669,269 0.1% 21 MB
chrY 175,008 9 174,999 0.0% 1.4 MB
total 71,111,240 84,844 71,026,396 0.1% 567 MB

Columns

column role type null % empty % distinct numeric (min / p50 / p95 / max) top values
protein_variant match String 0.00 0.00 ~902K
am_class value String 0.00 0.00 3 likely_benign (41M), likely_pathogenic (23M), ambiguous (7.9M)
am_pathogenicity value Float32 0.00 9,892 0.000 / 0.250 / 0.993 / 1.000

Usage

hf download biodatageeks/vepyr_116_GRCh38_plugin_alphamissense \
  --repo-type dataset --local-dir ~/vepyr_plugin_cache/plugin/alphamissense

The files are plain Parquet — usable directly from DuckDB, Polars or DataFusion independently of vepyr:

SELECT start, allele_string, protein_variant, am_class, am_pathogenicity
FROM 'chr21.parquet'
WHERE start BETWEEN 33000000 AND 33100000;

Licence

AlphaMissense data is © 2023 DeepMind Technologies Limited and licensed CC BY-NC-SA 4.0non-commercial use only, share-alike. This cache is a format conversion of that data and inherits those terms. The predictions themselves are unmodified.

AlphaMissense is intended for research use; it is not validated for direct clinical application.

Citation

Cheng, J., Novati, G., Pan, J., et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science 381, eadg7492 (2023). doi:10.1126/science.adg7492

Downloads last month
208