Agent skill · research science · k-dense-ai
polars-bio
High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Overlap, nearest, merge, coverage, complement, subtract for BED/VCF/BAM/GFF intervals. Streaming, cloud-native, faster bioframe alternative.
Why this skill is useful
Provides domain-specific knowledge for genomic interval operations and bioinformatics file I/O that the AI wouldn't reliably generate on its own.
What it needs
Requires polars-bio, python installed locally. About 8k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.
What this skill does
polars-bio Overview polars-bio is a high-performance Python library for genomic interval operations and bioinformatics file I/O, built on Polars, Apache Arrow, and Apache DataFusion. It provides a familiar DataFrame-centric API for interval arithmetic (overlap, nearest, merge, coverage, complement, subtract) and reading/writing common bioinformatics formats (BED, VCF, BAM, CRAM, GFF/GTF, FASTA, FASTQ). Key value propositions: 6-38x faster than bioframe on real-world genomic benchmarks Streaming/out-of-core support for large genomes via DataFusion Cloud-native file I/O (S3, GCS, Azure) with predicate pushdown Two API styles: functional (pb.overlap(df1, df2)) and method-chaining (df1.lazy().pb.overlap(df2)) SQL interface for genomic data via DataFusion SQL engine When to Use This Skill Use this skill when: Performing genomic interval operations (overlap, nearest, merge, coverage, complement, subtract) Reading/writing bioinformatics file formats (BED, VCF, BAM, CRAM, GFF/GTF, FASTA, FASTQ) Processing large genomic datasets that don't fit in memory (streaming mode) Running SQL queries on genomic data files Migrating from bioframe to a faster alternative Computing read depth/pileup from BAM/CRAM files Working with Polars DataFrames containing genomic intervals Quick Start Installation Requires Python 3.11–3.14 (see PyPI). For pandas compatibility (pandas ≥3.0): Basic Overlap Example Reading a BED File Core Capabilities 1. Genomic Interval Operations polars-bio provides 8 core interval operations for genomic range arithmetic. All operations accept Polars DataFrames with chrom, start, end columns (configurable). All operations return a LazyFrame by default (use outputtype="polars.DataFrame" for eager results). …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills k-dense-ai/polars-bio