Perform genomic interval arithmetic and bioinformatics I/O on Polars DataFrames.
npx skills add https://github.com/mkurman/tamux --skill polars-bio-mkurman
Please help me install this Agent Skill. Skill: polars-bio Source: https://github.com/mkurman/tamux/tree/main/skills/scientific-skills/polars-bio Command: npx skills add https://github.com/mkurman/tamux --skill polars-bio-mkurman
Polars-bio provides fast genomic interval operations and bioinformatics I/O on Polars DataFrames, enabling scalable interval arithmetic and cloud-enabled data processing for genomics.
Install polars-bio and run a basic overlap example to verify functionality.
High-intent search queries and answers about installing and using this skill.
Genomic interval overlap operations on large datasets are executed using Polars DataFrames. Polars-bio processes BED, VCF, BAM, and GFF formats, applying high-performance interval arithmetic to find overlapping genomic regions efficiently.
Streaming bioinformatics files directly from cloud storage is supported by polars-bio. It enables cloud-native data processing for genomics, allowing out-of-core computation on BED, VCF, BAM, and GFF formats without downloading entire datasets locally.
Finding nearest genomic intervals in Polars is best handled through the LazyFrame-oriented API. Polars-bio provides specific nearest interval operations, enabling scalable searches across large genomic datasets to identify adjacent features.
DataFusion integration supports querying registered genomic files and Polars DataFrames via SQL. This allows users to perform complex filtering and data extraction directly on bioinformatics file formats using standard SQL syntax.
Genomic interval arithmetic operations available for variant processing pipelines include overlap, nearest, merge, coverage, complement, and subtract. These operations run on Polars DataFrames to handle large-scale genome analysis.
Using Polars for bioinformatics file I/O provides high-performance, streaming-enabled interval operations. Polars-bio leverages Polars DataFrames and DataFusion to achieve scalable, out-of-core computation for genomic intervals that other frameworks may lack.
Estrella-231Perform genomic interval operations and bioinformatics file I/O on Polars DataFrames.
tassiovalePerform genomic interval arithmetic and bioinformatics file I/O on Polars DataFrames.
K-Dense-AIProcess genomic intervals with Polars DataFrames and DataFusion.
RamanEbrahimiPerform genomic interval operations and bioinformatics file I/O on Polars DataFrames.
