| name | alterlab-borzoi |
| description | Predict genome-wide functional genomics tracks from DNA sequence with Borzoi (Linder 2025) — a sequence-to-function model outputting RNA-seq, CAGE, ATAC, and ChIP coverage across long context, used to score non-coding and regulatory variant effects. Use when predicting functional tracks from a DNA sequence, scoring a non-coding/regulatory variant's effect on expression or chromatin, or doing in-silico mutagenesis of a locus. To LOOK UP a variant's population frequency prefer alterlab-gnomad; for its clinical significance prefer alterlab-clinvar; for protein-structure effects prefer alterlab-alphafold; for single-cell foundation models prefer alterlab-scgpt. Part of the AlterLab Academic Skills suite. |
| license | Apache-2.0 |
| allowed-tools | Read Write Edit Bash(python:*) Bash(uv:*) |
| compatibility | Runs Borzoi (`calico/borzoi`; install per repo — TODO(verify) exact pin) under `uv run python`. Model weights download once and cache; a CUDA GPU is recommended (the model takes long DNA context and is heavy on CPU). Inputs are DNA sequences (FASTA / genome coordinates + a reference); outputs are multi-track coverage arrays. Dispatch large scans via alterlab-remote-compute. |
| metadata | {"skill-author":"AlterLab","version":"1.0.0"} |
Borzoi (sequence → function)
Overview
Borzoi (Linder et al. 2025; calico/borzoi) is a sequence-to-function deep-learning
model: given a DNA sequence over a long genomic context, it predicts genome-wide functional
tracks — RNA-seq, CAGE, ATAC-seq, and ChIP coverage across many assays/tissues. Its headline
use is non-coding variant effect scoring: run the reference and alternate alleles through
the model and compare predicted tracks to estimate a regulatory variant's impact on expression
or chromatin.
It predicts function from sequence; it does not look up known variants. For a variant's
population frequency use alterlab-gnomad; for clinical significance use alterlab-clinvar.
When to Use This Skill
Use this skill when the user wants to:
- Predict functional tracks (RNA-seq/CAGE/ATAC/ChIP) from a DNA sequence or locus.
- Score a non-coding / regulatory variant's predicted effect (ref vs. alt).
- Run in-silico mutagenesis to find driver bases in a regulatory element.
- Prioritize candidate regulatory variants by predicted functional impact.
Does NOT Trigger
| Scenario | Use instead |
|---|
| Look up a variant's population frequency | alterlab-gnomad |
| Look up a variant's clinical significance | alterlab-clinvar |
| Predict a protein-structure / coding effect | alterlab-alphafold |
| Single-cell foundation-model tasks | alterlab-scgpt |
| Standard variant calling from reads | alterlab-nf-core-sarek (or the relevant pipeline skill) |
Core Capabilities
1. Track prediction from sequence
