polars-bio

Perform genomic interval operations and bioinformatics I/O on Polars DataFrames.

Updated Aug 23, 2026

Search Tags:#streaming #bioinformatics #genomics #polars #datafusion #genomic-intervals

Ready to run

npx skills add https://github.com/must1f/Dissertaion-Project --skill polars-bio-must1f

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: polars-bio
Source: https://github.com/must1f/Dissertaion-Project/tree/main/.agents/skills/polars-bio
Command: npx skills add https://github.com/must1f/Dissertaion-Project --skill polars-bio-must1f

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Polars-bio delivers high-performance genomic interval arithmetic and bioinformatics file I/O for Polars DataFrames, enabling scalable analyses on large genomic datasets and seamless integration with cloud storage.

Core Features & Use Cases

Genomic interval operations (overlap, nearest, merge, coverage, complement, subtract) on Polars DataFrames with coordinate system support and streaming/out-of-core processing.
Bioinformatics file I/O across BED, VCF, BAM/CRAM, GFF/GTF, FASTA/FASTQ, SAM, Hi-C pairs, plus SQL processing with the pb.sql interface.
Flexible API styles including functional usage pb.overlap(...) and method-chaining via df.lazy().pb.* for scalable pipelines.

Quick Start

Install polars-bio, import polars_bio as pb, and run a simple overlap on two interval DataFrames.

Frequently Asked Questions about polars-bio

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform genomic interval overlap operations on large Polars DataFrames?▼

Genomic interval overlap operations on large Polars DataFrames are performed using polars-bio, which provides streaming and out-of-core processing for scalable analysis. It supports functional API calls like pb.overlap() and method-chaining via LazyFrame integration.

Can I read and write bioinformatics file formats like BED, VCF, and BAM in Polars?▼

Yes, reading and writing bioinformatics file formats like BED, VCF, BAM, CRAM, and GFF in Polars is supported natively. Polars-bio handles comprehensive bioinformatics I/O directly within DataFrames, enabling seamless integration into large-scale genomics workflows.

Does Polars support streaming and out-of-core processing for genomic intervals?▼

Polars supports streaming and out-of-core processing for genomic intervals through polars-bio, enabling scalable analysis on large genomic datasets. It leverages a lazy, cloud-enabled analytics framework to handle operations that exceed memory limits.

What is the best way to run SQL queries on bioinformatics data in Polars?▼

The best way to run SQL queries on bioinformatics data in Polars is using the pb.sql interface provided by polars-bio. It enables SQL data processing directly on genomic intervals and bioinformatics file formats within a streaming-capable environment.

Are nearest, merge, and coverage operations available for genomic intervals in Polars?▼

Nearest, merge, coverage, complement, and subtract operations are all available for genomic intervals in Polars. Polars-bio provides these interval arithmetic functions with coordinate system support to enable complex large-scale genomics workflows.

How do I integrate cloud storage with bioinformatics I/O and Polars DataFrames?▼

Cloud storage integration with bioinformatics I/O and Polars DataFrames is handled natively by polars-bio. It enables seamless analysis of large genomic datasets directly from cloud environments using a lazy, streaming-capable architecture.