borzoi
Predict genome-wide functional tracks (RNA-seq, CAGE, DNase, ChIP) from DNA sequence with Borzoi. Use this skill when: (1) Scoring the regulatory effect of a variant on expression/accessibility, (2) Generating predicted coverage tracks for a locus, (3) Prioritising non-coding variants by predicted track delta.
Profile →npx skills add xuzhougeng/wisp-science --skill borzoi --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Borzoi — DNA → Functional Track Prediction ## Prerequisites | Requirement | Minimum | Recommended | | ----------- | ------- | ----------- | | Python | 3.10+ | 3.11 | | CUDA | 12.1+ | 12.4+ | | GPU VRAM | 16 GB | 24 GB+ | ## How to run ```python from borzoi_pytorch import Borzoi model = Borzoi.from_pretrained("johahi/borzoi-replicate-0").cuda().eval() # input: (batch, 4, 524288) one-hot DNA → output: (batch, tracks, 6144) bins ``` Borzoi consumes ~524 kb one-hot windows and emits binned predictions across 7,611 human tracks (the separate 2,608-track mouse head is off by default; enable via `enable_mouse_head=True` and select with `forward(..., is_human=False)`). For variant scoring, run ref/alt windows centred on the variant and compare per-track output. ## Output format `(B, T, L)` tensor — `T` tracks × `L` 32-bp bins. Track metadata (assay, biosample) is in `borzoi_pytorch.pytorch_borzoi_model.TRACKS_DF` (or `model.tracks_df` when using the `AnnotatedBorzoi` subclass) — the base `Borzoi` model has no `targets` attribute. ## Remote compute Needs ≥24 GB VRAM and either pre-cached HF weights or egress to `huggingface.co`. Use a selected and probed `ssh:<alias>` context and load `re
- Prerequisites
- How to run
- Output format
- Remote compute
- Troubleshooting
What does the borzoi skill do?
Predict genome-wide functional tracks (RNA-seq, CAGE, DNase, ChIP) from DNA sequence with Borzoi. Use this skill when: (1) Scoring the regulatory effect of a variant on expression/accessibility, (2) Generating predicted coverage tracks for a locus, (3) Prioritising non-coding variants by predicted track delta.
How do I install it?
Run `npx skills add xuzhougeng/wisp-science --skill borzoi --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From xuzhougeng/wisp-science, a repository with 895 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.