GenomicsGPU5 credits

AlphaGenome — DNA Variant Effect Prediction

Predict how DNA variants affect gene expression, splicing, and regulation

AlphaGenome (DeepMind, 2026) predicts the functional impact of DNA variants on gene regulation. It analyzes how single nucleotide variants and short indels affect gene expression levels, mRNA splicing, chromatin accessibility, and transcription factor binding across multiple tissues. Published in Nature, AlphaGenome achieves state-of-the-art performance on genomic variant effect benchmarks.

$0.05

per API call

credits per call

/v1/genomics/alphagenome

API endpoint

Features

Gene expression effect prediction (log2 fold change per tissue)

Splicing change prediction (delta PSI)

Chromatin accessibility impact scoring

Regulatory element disruption detection

Transcription factor binding change prediction

Multi-tissue analysis (5+ tissue types)

Quick Start

AlphaGenome (DeepMind) — Python Examplepython

import requests

API_KEY = "sk-sci-your-key-here"
url = "https://scirouter.ai/v1/genomics/alphagenome"

response = requests.post(url, json={
    "variants": [
        {"chromosome": "chr17", "position": 41245466, "ref": "A", "alt": "G", "gene": "BRCA1"},
        {"chromosome": "chr7", "position": 140753336, "ref": "A", "alt": "T", "gene": "BRAF"}
    ],
    "genome_build": "GRCh38",
    "tissues": ["liver", "brain", "blood"]
}, headers={"Authorization": f"Bearer {API_KEY}"})

result = response.json()["data"]
for v in result["variants"]:
    expr = v["predictions"]["expression_effect"]
    print(f"{v['variant']['gene']}: {expr['direction']} "
          f"(log2FC={expr['log2_fold_change']:.2f}, "
          f"confidence={expr['confidence']:.2f})")
    print(f"  Severity: {v['overall_assessment']['severity']}")