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Machine learning51k · #1883

gtars

Helps your agent work with genomic data. It supports genomic interval models, set algebra, and fragment processing across multiple languages.

What it does

Gtars is a tool for working with genomic data. It helps analyze and manipulate information about DNA sequences and other parts of genomes.

When to use it

  • ✓When you need to compare different regions within a genome.
  • ✓When counting how many times a specific sequence appears.
  • ✓To efficiently process and organize genomic data.

Example of what to ask your AI

“How can I use Gtars to find overlapping regions between two genomic files?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/gtars/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/gtars/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

Gtars uses code written in Rust and Python to perform its tasks. It checks genomic data to ensure it's correct before processing it.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add K-Dense-AI/scientific-agent-skills --skill gtars

Or download just the file:

curl -L https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/gtars/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Gtars

Gtars provides native Rust implementations, Python bindings, and a feature-gated gtars binary for genomic interval and reference-sequence work. Start with the bundled local inspectors; call upstream code only after the data contract, provenance, resource bounds, and side effects are explicit.

Verified snapshot (2026-10-01)

  • Published Python wheel: gtars==0.10.0, released 2026-09-05, Requires-Python >=3.10; local examples were exercised on Python 3.12 with synthetic intervals, fragments, and FASTA.
  • Rust meta-crate and CLI: gtars=0.10.0 and gtars-cli=0.10.0, released 2026-09-05. The binary is gtars; the wrapper's default feature set is empty. Rust/CLI examples are source-reviewed templates, not compiled executions.
  • Direct gtars-refget=0.11.0 was released 2026-09-22. Its Rust list_sequences() now returns a Result. The wrapper requests refget 0.10.x; keep Cargo.lock because component dependencies use compatible ranges, not exact pins.
  • A gtars-python-v0.11.0 Git tag exists, but PyPI still publishes 0.10.0. Do not assume that Git tags, Python packages, components, or CLI versions coincide.
  • Published guides contain older examples. This review used the PyPI 0.10.0 source distribution/runtime, published CLI crate source, and current releases.

The license: MIT field covers this skill. Published gtars crates declare MIT, while the GitHub repository currently displays BSD-2-Clause at the root; verify the exact artifact's license before redistribution.

Native-code trust gate and exact pins

The Python wheel contains a PyO3 native extension. Cargo installation compiles a native binary and can run dependency build scripts. Treat either path as code execution:

  1. Confirm the official PyPI/crates.io/GitHub owner and immutable version.
  2. Review filenames, platform tags, release provenance, license, and SHA-256. Verify checksums from the exact release; do not reuse older binary archives.
  3. Never run an untrusted prebuilt binary, wheel, source tree, Cargo build script, or archive installer. Use isolation and CPU/RAM/disk/time limits.
  4. Keep a lockfile and artifact hashes with the analysis manifest.

After that review, create an isolated Python environment:

uv venv --python 3.11 .venv-gtars
uv pip install --dry-run --python .venv-gtars/bin/python "gtars==0.10.0"
uv pip install --python .venv-gtars/bin/python "gtars==0.10.0"
.venv-gtars/bin/python -c \
  "import gtars; assert gtars.__version__ == '0.10.0'; print(gtars.__version__)"

For the source-reviewed CLI release (installation template, not run in this audit):

cargo install gtars-cli --version 0.10.0 --locked
gtars --version
gtars --help

For a Rust project, this source-reviewed template pins the wrapper and enables only required features; retain Cargo.lock for transitive versions:

[dependencies]
gtars = { version = "=0.10.0", default-features = false, features = [
  "core", "overlaprs", "uniwig", "tokenizers", "refget"
] }

Use gtars-refget = "=0.11.0" directly only when the newer direct component API is required and compatibility has been tested. Do not replace these pins with a Git branch or an unreviewed release.

Genomic data contract

Apply this contract before every operation:

  1. Coordinates: BED intervals are 0-based and half-open: [start, end). Require 0 <= start < end <= contig_length. Gtars coordinates are u32, so reject values above 4,294,967,295.
  2. Assembly: record an assembly accession/version and the SHA-256 of the exact chromosome-sizes or refget sequence-collection metadata. Never infer assembly from filenames or chr prefixes.
  3. Contigs: compare names exactly. 1 and chr1, alternate loci, decoys, and mitochondrial aliases are not interchangeable. Rename or liftover only as a separately reviewed transformation.
  4. Sorting: preserve the original file, then sort a copy by chromosome-sizes order and numeric start/end when the operation requires it. Python RegionSet(path) currently sorts lexicographically by contig and start while loading; do not rely on original row order afterward. Construction does not

…

FAQ

What are 'genomic intervals'?

They are like markers on a DNA sequence, indicating a start and end of a region of interest.

What does 'set algebra' mean in this context?

It's like using mathematical operations (union, intersection, difference) to combine or compare sets of genomic regions.

Why is it important to check data 'provenance'?

To know the exact origin of the genomic data and ensure it is reliable and has been processed correctly.

Details

Original description by the author

Supports Gtars for local genomic interval models and set algebra, overlaps and counts, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and the CLI.

repo: K-Dense-AI/scientific-agent-skills

Popularity

GitHub stars
51k
Ranking position
#1883
License
MIT
Updated
10/15/2026

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