alphagenome-single-variant-analysis

Name: alphagenome-single-variant-analysis
Availability: InStock
Author: NeuroAIHub

Analyze non-coding variant effects on expression, chromatin, and splicing via AlphaGenome API.

269|20|Updated Jun 13, 2026

Search Tags:#genomics #genetics #variant analysis #regulatory #splicing #alphagenome

Ready to run

npx skills add https://github.com/NeuroAIHub/BrainPilot --skill alphagenome-single-variant-analysis-neuroaihub

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: alphagenome-single-variant-analysis
Source: https://github.com/NeuroAIHub/BrainPilot/tree/main/packages/skills/skills/18_Genetics_Genomics/alphagenome-single-variant-analysis
Command: npx skills add https://github.com/NeuroAIHub/BrainPilot --skill alphagenome-single-variant-analysis-neuroaihub

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires alphagenome, absl-py, python-dotenv, matplotlib, numpy, pandas, pyarrow, scipy, seaborn, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill addresses the complexity of interpreting non-coding genetic variants by providing a standardized, automated pipeline to predict their functional impact on gene expression, chromatin accessibility, and splicing.

Core Features & Use Cases

Variant Effect Prediction: Analyze how specific variants (chr:pos:ref>alt) influence regulatory elements like promoters and enhancers.
Splicing Analysis: Quantify changes in splice site usage and identify potential exon skipping or cryptic junction events.
Mechanistic Interpretation: Generate In-Silico Mutagenesis (ISM) sequence logos to identify disrupted transcription factor binding motifs.
Use Case: A researcher investigating a novel variant in a patient with a suspected regulatory disorder can use this skill to determine if the variant disrupts a tissue-specific enhancer or creates a cryptic splice site in a relevant cell type.

Quick Start

Use the alphagenome-single-variant-analysis skill to analyze the functional effects of the variant chr17:7675148:G>A in liver tissue using the UBERON:0002107 ontology.

Frequently Asked Questions about alphagenome-single-variant-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze the functional impact of non-coding genetic variants on gene expression?▼

To analyze non-coding genetic variants, this skill uses the AlphaGenome API to predict functional impacts on gene expression, chromatin accessibility, and splicing. You provide variants in chr:pos:ref>alt format to score their effects on regulatory elements.

Can I quantify changes in splice site usage for specific genetic variants?▼

Yes, you can quantify splicing changes by evaluating genetic variants with the AlphaGenome API. This skill identifies potential exon skipping or cryptic junction events and calculates quantitative splicing differences for the provided variant coordinates.

How does In-Silico Mutagenesis identify disrupted transcription factor binding motifs?▼

In-Silico Mutagenesis (ISM) identifies disrupted motifs by systematically altering sequence bases and generating sequence logos. This mechanistic interpretation reveals exactly how a genetic variant affects transcription factor binding within regulatory regions.

Do I need local GTF data and API credentials to predict variant effects with AlphaGenome?▼

Yes, you need valid AlphaGenome API credentials and local GTF data. The GTF data is required for gene annotation and transcript lookup to accurately map and analyze the functional impact of your input variants.

What is the best way to score high-throughput non-coding variants for regulatory disorders?▼

The best way to score high-throughput variants is using this automated pipeline with the AlphaGenome API. It standardizes the prediction of variant impacts on tissue-specific enhancers and promoters, requiring relevant tissue ontologies like UBERON for context.