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geniml

Plans and audits local genomic-interval machine learning workflows with Geniml (0.8.4) and Gtars: validates BED files against chromosome sizes and assembly contracts, plans Region2Vec, scEmbed, and BEDspace runs, checks model, tokenizer, and universe.bed compatibility, and assesses consensus universes (CC, CCF, ML, HMM, assess-universe). Bundled scripts only validate or plan; they do not train. Use when checking BED coordinates, contigs, or assembly before analysis. Use when planning Region2Vec or scEmbed training on tokenized Parquet data. Use when verifying that a checkpoint, config.yaml, and universe match. Use when building or assessing a consensus peak universe. Use when reviewing BEDbase or Hugging Face download risks. Not for general BED manipulation or peak calling; use bedtools or similar tools.

plugins/KalarisLabs/research-agent-skills/skills/geniml/SKILL.md

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Nov 6, 2026
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Apache-2.0

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# Geniml

Use Geniml for machine learning and statistical workflows over genomic interval
sets. Treat coordinates, assemblies, token vocabularies, model artifacts, and
sample grouping as explicit contracts. The bundled scripts validate or plan;
they do not import Geniml, contact services, deserialize models, or execute
training.

`Bash` is declared only for explicit, user-approved `uv`, Python, Geniml,
Gtars, Git, and native CLI commands shown in this guide; bundled Python helpers
do not spawn subprocesses. Example paths under `data/`, `refs/`, `work/`, and
`models/` are user-provided project placeholders, not missing bundled files.

## Verified release snapshot