Skills

Gtars

High-performance toolkit for genomic interval analysis in Rust with Python bindings.

Install

npx skills add LeonChaoX/qinyan-academic-skills --skill gtars -g -a claude-code -y
Category
Data and ML
Updated
4mo ago
License
Unknown
Context cost
Mediumabout 1,858 tokens
Runs scripts
No, instructions only

What it does

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Gtars: Genomic Tools and Algorithms in Rust

Overview

Gtars is a high-performance Rust toolkit for manipulating, analyzing, and processing genomic interval data. It provides specialized tools for overlap detection, coverage analysis, tokenization for machine learning, and reference sequence management.

Use this skill when working with:

  • Genomic interval files (BED format)
  • Overlap detection between genomic regions
  • Coverage track generation (WIG, BigWig)
  • Genomic ML preprocessing and tokenization
  • Fragment analysis in single-cell genomics
  • Reference sequence retrieval and validation

Installation

Python Installation

Install gtars Python bindings:

uv uv pip install gtars

CLI Installation

Install command-line tools (requires Rust/Cargo):

# Install with all features
cargo install gtars-cli --features "uniwig overlaprs igd bbcache scoring fragsplit"

# Or install specific features only
cargo install gtars-cli --features "uniwig overlaprs"

Rust Library

Add to Cargo.toml for Rust projects:

[dependencies]
gtars = { version = "0.1", features = ["tokenizers", "overlaprs"] }

Core Capabilities

Gtars is organized into specialized modules, each focused on specific genomic analysis tasks:

1. Overlap Detection and IGD Indexing

Efficiently detect overlaps between genomic intervals using the Integrated Genome Database (IGD) data structure.

When to use:

  • Finding overlapping regulatory elements
  • Variant annotation
  • Comparing ChIP-seq peaks
  • Identifying shared genomic features

Quick example:

import gtars

# Build IGD index and query overlaps
igd = gtars.igd.build_index("regions.bed")
overlaps = igd.query("chr1", 1000, 2000)

See references/overlap.md for comprehensive overlap detection documentation.

2. Coverage Track Generation

Generate coverage tracks from sequencing data with the uniwig module.

Read the whole SKILL.md on GitHub

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