allelix/allelix-alphamissense
Allelix AlphaMissense Pathogenicity Cache Pre-built SQLite cache of missense variant pathogenicity predictions from DeepMind's AlphaMissense for use with Allelix. What's in the file alphamissense.sqlite.gz is a gzipped SQLite database containing the alphamissense_scores table with all ~71M missense variant predictions from AlphaMissense, 7.5M of which carry rsID mappings via a gnomAD v4.1 coordinate join. Schema CREATE TABLE alphamissense_scores (… See the full description on the dataset page: https://huggingface.co/datasets/allelix/allelix-alphamissense.
Allelix AlphaMissense Pathogenicity Cache
Pre-built SQLite cache of missense variant pathogenicity predictions from DeepMind's AlphaMissense for use with Allelix.
What's in the file
alphamissense.sqlite.gz is a gzipped SQLite database containing the alphamissense_scores table with all ~71M missense variant predictions from AlphaMissense, 7.5M of which carry rsID mappings via a gnomAD v4.1 coordinate join.
Schema
CREATE TABLE alphamissense_scores (
chrom TEXT NOT NULL,
pos INTEGER NOT NULL,
ref TEXT NOT NULL,
alt TEXT NOT NULL,
rsid TEXT,
uniprot_id TEXT,
transcript_id TEXT,
protein_variant TEXT,
am_pathogenicity REAL NOT NULL,
am_class TEXT NOT NULL,
PRIMARY KEY (chrom, pos, ref, alt)
);
CREATE INDEX idx_am_rsid ON alphamissense_scores(rsid);Columns
Multi-allelic sites
The composite primary key (chrom, pos, ref, alt) preserves multi-allelic sites. A single rsID may have multiple rows with different alternate alleles and divergent pathogenicity scores. For example, chr1:69094 has G→T (0.294, likelybenign) and G→C (0.981, likelypathogenic) at the same position.
How Allelix uses this
Allelix downloads this file automatically during allelix db update. The enrichment annotator looks up variants by rsID and returns MAX(am_pathogenicity) across alleles for a given rsID. The AM Score column appears in terminal, HTML, and JSON reports. AlphaMissense scores reflect predicted protein structural impact only — not clinical or pharmacogenomic significance.
Building from source
The cache can be rebuilt from the AlphaMissense Zenodo TSV using the build script included with Allelix:
python scripts/build_alphamissense_cache.py --tsv AlphaMissense_hg38.tsv.gz --output alphamissense.sqlite
gzip alphamissense.sqliteThe build script joins against the gnomAD cache (if present) to populate rsID mappings. Without gnomAD, all rsID fields will be NULL and the annotator will not match any variants by rsID.
Source and license
- Source: AlphaMissense (Cheng et al., Science 2023, Google DeepMind)
- License: Creative Commons Attribution 4.0 (CC BY 4.0)
- Citation: Cheng J, Novati G, Pan J, et al. Accurate proteome-wide missense variant effect prediction with AlphaMissense. Science. 2023;381(6664):eadg7492.
