Predict the regulatory impact of a genetic variant using AlphaGenome AI.

Powered by Google DeepMind's AlphaGenome model for accurate regulatory predictions.

Analyzes how a single nucleotide change affects:

• Gene expression (RNA-seq predictions)

• Splicing patterns

• Transcription factor binding

• Chromatin accessibility

• Histone modifications

Perfect for: variant interpretation, GWAS follow-up, clinical genomics research.

Example: "Analyze chr17:41234567A>T with AlphaGenome"

Score and prioritize multiple genetic variants using AlphaGenome AI.

Powered by Google DeepMind's AlphaGenome model for high-throughput variant scoring.

Analyzes up to 100 variants simultaneously and ranks them by regulatory impact.

Scoring metrics:

• rna_seq: Gene expression changes

• splice: Splicing alterations

• regulatory_impact: Combined regulatory score

• combined: All metrics weighted

Perfect for: GWAS post-analysis, VCF filtering, variant prioritization.

Example: "Score these 50 variants and show me the top 10 by regulatory impact"

Comprehensive pathogenicity assessment of a genetic variant.

Evaluates variant across all regulatory modalities and provides clinical classification.

Returns:

• Pathogenicity score (0-1 scale)

• Clinical classification (pathogenic/likely_pathogenic/uncertain/likely_benign/benign)

• Evidence breakdown (expression, splicing, TF binding impacts)

Perfect for: clinical variant interpretation, pathogenicity prediction, diagnostic sequencing.

Example: "Assess pathogenicity of chr19:44908684T>C"

Predict variant effects across multiple tissues.

Compares regulatory impact in different tissues to identify tissue-specific effects.

Default tissues: brain, liver, heart (customizable)

Returns impact levels and expression changes for each tissue.

Perfect for: understanding tissue-specific disease mechanisms, prioritizing relevant tissues.

Example: "Compare rs429358 effects in brain, liver, and heart"

Compare two variants side-by-side.

Direct comparison of regulatory impacts between two variants.

Returns:

• Impact levels for both variants

• Expression and splicing changes

• Which variant is more severe

Perfect for: comparing candidate variants, understanding relative severity.

Example: "Compare rs429358 vs rs7412"

Focus on splicing-specific effects only.

Analyzes splice sites, splice site usage, and splice junctions.

Perfect for: investigating splicing variants, understanding splice alterations.

Example: "Analyze splicing impact of chr6:41129252C>T"

Focus on gene expression effects only.

Analyzes RNA-seq and CAGE predictions for expression changes.

Perfect for: eQTL analysis, expression-related variants.

Example: "Analyze expression impact of rs744373"

Analyze all variants in a GWAS locus.

Ranks variants by regulatory impact for fine-mapping and causal variant identification.

Perfect for: GWAS follow-up, fine-mapping, identifying causal variants.

Example: "Analyze GWAS locus with 10 variants"

Compare different alleles at the same position.

Useful for understanding effects of different mutations at a hotspot position.

Example: "Compare T>C vs T>G vs T>A at chr19:44908684"

Analyze multiple variants across multiple tissues.

Efficient batch analysis of variants × tissues combinations.

Perfect for: large-scale tissue-specificity studies.

Example: "Test 10 variants in brain, liver, heart"

Focus on transcription factor binding effects only.

Analyzes TF binding site changes using ChIP-seq predictions.

Perfect for: TF binding site variants, regulatory element analysis.

Example: "Analyze TF binding impact of chr1:12345678G>A"

Focus on chromatin accessibility effects only.

Analyzes DNase and ATAC-seq predictions for chromatin state changes.

Perfect for: enhancer variants, regulatory region analysis.

Example: "Analyze chromatin impact of chr2:23456789C>T"

Compare protective vs risk alleles directly.

Side-by-side comparison of alleles with opposite disease associations.

Perfect for: disease mechanism studies, therapeutic target identification.

Example: "Compare APOE protective allele vs risk allele"

Filter variants by pathogenicity threshold.

Efficiently identifies pathogenic variants from large lists.

Perfect for: VCF filtering, prioritizing clinical variants.

Example: "Filter 100 variants for pathogenicity > 0.7"

Compare multiple variants within the same gene.

Ranks variants by impact within a single gene context.

Perfect for: gene-level analysis, compound heterozygote analysis.

Example: "Compare 5 BRCA1 variants"

Analyze allele-specific regulatory effects.

Detailed analysis of how each allele affects gene regulation differently.

Perfect for: ASE analysis, imprinting studies.

Example: "Analyze allele-specific effects of chr15:67890123A>G"

Provide comprehensive regulatory annotation for a variant.

Returns detailed regulatory context including all modalities.

Perfect for: variant annotation pipelines, comprehensive reports.

Example: "Annotate regulatory context of chr7:12345678C>A"

Screen variants across specific regulatory modalities.

Efficiently tests multiple variants for specific regulatory effects.

Perfect for: targeted regulatory screens, modality-specific studies.

Example: "Screen 20 variants for splicing effects"

Generate comprehensive clinical report for a variant.

Full analysis with all modalities and clinical interpretation.

Perfect for: clinical reports, diagnostic summaries.

Example: "Generate full report for chr13:32912345G>T"

Provide human-readable explanation of variant impact.

Translates technical predictions into plain language.

Perfect for: patient reports, non-technical summaries.

Example: "Explain the impact of chr9:12345678A>C in simple terms"