Process genomic interval data and bioinformatics files in Polars.
npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill polars-bio-jasrajtulsi
Please help me install this Agent Skill. Skill: polars-bio Source: https://github.com/jasrajtulsi/GRAD-SCOPE/tree/main/.claude/skills/polars-bio Command: npx skills add https://github.com/jasrajtulsi/GRAD-SCOPE --skill polars-bio-jasrajtulsi
This Skill removes the friction of working with genomic interval data and bioinformatics files by giving you fast, Polars-native tools for overlap analysis, nearest-neighbor lookup, interval merging, coverage, subtraction, complement, and depth calculation.
Ask the assistant to use polars-bio to load your genomic files, run the interval or file I/O operation you need, and return the result as a Polars DataFrame.
High-intent search queries and answers about installing and using this skill.
Genomic interval overlap analysis in Polars is performed by loading BED-like interval sets and applying operations such as overlap, count_overlaps, nearest, merge, and subtract directly on the DataFrames.
Yes, you can read, scan, write, and stream common bioinformatics files including VCF, BAM, CRAM, BED, GFF, GTF, FASTA, FASTQ, and SAM using Polars-native lazy execution and optional cloud I/O.
Querying large genomic datasets with SQL is done by registering interval DataFrames as SQL tables and executing DataFusion SQL queries, leveraging LazyFrame-based execution and streaming for large-scale workflows.
Polars supports coverage, complement, subtract, and depth calculation for BED files and other genomic interval sets, allowing you to summarize interval properties without leaving the Polars ecosystem.
Finding nearest regulatory regions uses the nearest-neighbor lookup operation on genomic interval sets, enabling you to rank proximal regions by distance directly within Polars DataFrames.
Yes, LazyFrame-based execution is required for processing large-scale bioinformatics datasets, with optional streaming and coordinate metadata handling to efficiently manage large files and cloud storage inputs.
mkurmanPerform genomic interval arithmetic and bioinformatics I/O on Polars DataFrames.
tassiovalePerform genomic interval arithmetic and bioinformatics file I/O on Polars DataFrames.
crazymsnPerform genomic interval arithmetic and bioinformatics I/O within Polars DataFrames.
Estrella-231Perform genomic interval operations and bioinformatics file I/O on Polars DataFrames.
