gtars
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.
npx skills add majiayu000/claude-skill-registry --skill gtars-hxk622-tokendance-2 --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.
# 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: ```bash uv uv pip install gtars ``` ### CLI Installation Install command-line tools (requires Rust/Cargo): ```bash # 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: ```toml [dependencies] gtars = { version = "0.1", features = ["tokenizers", "overlaprs"] } ``` ## Core Capabilities Gtars is organized into specialized mo
- Overview
- Installation
- Python Installation
- CLI Installation
- Rust Library
- Core Capabilities
- 1. Overlap Detection and IGD Indexing
- 2. Coverage Track Generation
- 3. Genomic Tokenization
- 4. Reference Sequence Management
- 5. Fragment Processing
- 6. Fragment Scoring
- Common Workflows
- Workflow 1: Peak Overlap Analysis
uv uv pip install gtars 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" Generate BigWig coverage track gtars uniwig generate --input fragments.bed --output coverage.bw --format bigwig Split fragments by clusters gtars fragsplit cluster-split --input fragments.tsv --clusters clusters.txt --output-dir ./by_cluster/ Score fragments against reference
What does the gtars skill do?
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.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill gtars-hxk622-tokendance-2 --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 majiayu000/claude-skill-registry, a repository with 534 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.