gtars — high-performance Rust toolkit for genomic interval analysis with Python bindings
Rust toolkit for genomic intervals — IGD overlap detection, uniwig coverage tracks, ML tokenization, GA4GH refget sequence management, fragment processing and scoring; Python API, CLI, and Rust library
- What
- Rust toolkit for genomic intervals — IGD overlap detection, uniwig coverage tracks, ML tokenization, GA4GH refget sequence management, fragment processing and scoring; Python API, CLI, and Rust library
- Cost
- Free
- Needs
- genomic interval data (BED files) and either Python (uv) or a Rust toolchain — the skill is a workflow guide for the gtars toolkit, not the software itself
- Install
- Copy the installer prompt below into your Muse — your agent does the rest.
Curated by Skill Harbor — @davila7's gtars skill: a practical guide to gtars, the high-performance Rust toolkit (with Python bindings) for genomic interval analysis. Six modules: IGD-indexed overlap detection and set operations; uniwig coverage-track generation (WIG/BigWig); genomic tokenization for ML (TreeTokenizer, integration with geniml); GA4GH refget reference-sequence management and digests; fragment processing (fragsplit cluster splits for single-cell); and fragment scoring against references. Includes installation for all three surfaces (uv pip for Python, cargo install for the CLI, Cargo.toml for the Rust library), three full workflows (peak-overlap analysis, coverage-track pipeline, ML preprocessing), Python-vs-CLI usage guidance, performance characteristics (native Rust, multi-threaded, zero-copy NumPy), supported formats (BED, WIG/BigWig, FASTA, fragment TSV), and error handling. Honest caveats: a scientific-computing skill — the CLI requires a Rust toolchain; it's the foundation layer under geniml, use it for preprocessing and tokenization. MIT per the discovery manifest (the skill frontmatter states no license — the manifest makes faith). Skill Harbor never reviews the code, review it yourself before use. Discovered via skills.sh.
Version:
Install
Prerequisites: genomic interval data (BED files) and either Python (uv) or a Rust toolchain — the skill is a workflow guide for the gtars toolkit, not the software itself Install "gtars — high-performance Rust toolkit for genomic interval analysis with Python bindings" for me. It gives my agent @davila7's gtars workflow: install via uv pip, cargo install, or Cargo.toml, detect overlaps with IGD indexing, generate uniwig coverage tracks, tokenize genomic regions for ML (TreeTokenizer), manage reference sequences via GA4GH refget, process and score fragments — with full workflows (peak-overlap analysis, coverage pipeline, ML preprocessing), Python-vs-CLI guidance, and debugging. Foundation layer under geniml: use it for preprocessing and tokenization. MIT-licensed (per the discovery manifest; the skill frontmatter states no license). Repository: https://github.com/davila7/claude-code-templates/blob/main/cli-tool/components/skills/scientific/gtars/SKILL.md 1. Fetch the SKILL.md file (and any helper files) from the repository path into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "gtars". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. install gtars via uv or cargo myself and provide my BED files; nothing else — it's a methodology). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. If anything looks off, stop and ask me.
Questions
How do I install a build?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you — no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.
What does the ✓ next to a creator’s name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a build before installing it.