Compute genomic interval overlaps, merges, and coverage on Polars DataFrames.
npx skills add https://github.com/dralkh/seerai --skill polars-bio-dralkh
Please help me install this Agent Skill. Skill: polars-bio Source: https://github.com/dralkh/seerai/tree/main/skills/polars-bio Command: npx skills add https://github.com/dralkh/seerai --skill polars-bio-dralkh
This Skill removes the friction of working with genomic intervals and bioinformatics files by turning common research operations into fast, composable Polars workflows.
Ask the assistant to load my genomic files, run the relevant interval or file I/O operation, and return the result as a Polars table.
High-intent search queries and answers about installing and using this skill.
To find genomic interval overlaps, you compute them directly on Polars DataFrames using LazyFrames and DataFusion-backed metadata. It supports overlaps, nearest neighbors, merges, coverage, and subtraction across genomic regions.
Yes, you can stream large VCF and BAM files. The system supports bioinformatics file I/O with streaming scans, allowing you to process large-scale BED, VCF, BAM, CRAM, and SAM datasets efficiently without loading everything into memory.
Polars supports reading cloud-native genomic data formats via cloud URIs. You can read, scan, and write BED, VCF, BAM, CRAM, GFF/GTF, FASTA, FASTQ, SAM, and Hi-C pairs data directly from cloud storage for research workflows.
To calculate pileup depth and coverage gaps, scan your BAM file and use the interval coverage and complement operations. This computes read depth across target regions and identifies gaps for downstream review.
The best way to query genomic intervals with SQL is to register your datasets as tables and run SQL queries directly against them. This integrates with DataFusion-backed interval metadata for flexible research analysis.
When subtracting genomic intervals, coordinate systems must be explicitly configured to ensure deterministic results. You need Polars LazyFrames and DataFusion-backed interval metadata to correctly compute subtractive differences at scale.
astronomerQuery data warehouses with SQL and return Polars/Pandas dataframes.
mako-aiWrite PostgreSQL dialect-compliant SQL queries with correct identifiers, casts, JSON operators, arrays, and intervals.
Lord1EgyptPerform genomic interval arithmetic and stream BED, VCF, and BAM files with Polars.
Estrella-231Perform genomic interval operations and bioinformatics file I/O on Polars DataFrames.
