Does Pysam use 0-based or 1-based coordinates?

Pysam primarily uses 0-based, half-open coordinates following Python convention. However, region strings used in fetch() operations follow the 1-based samtools convention for consistency with command-line tools.

Can I run samtools commands directly through this skill?

Yes, Pysam provides a Python wrapper for the samtools and bcftools suites, allowing you to perform operations like sorting, indexing, and merging files without leaving your Python environment.

What genomic file formats does the Pysam skill support?

Pysam supports all major bioinformatics formats including SAM, BAM, and CRAM for sequence alignments, VCF and BCF for genetic variants, and FASTA and FASTQ for reference sequences and raw reads.

Why are index files required for Pysam operations?

Index files (such as .bai, .crai, or .tbi) are necessary for random access. They allow Pysam to jump directly to specific genomic coordinates without reading the entire file, which is critical for performance with large datasets.

Pysam Bioinformatics Toolkit

Name: Pysam Bioinformatics Toolkit
Author: lifangda

bylifangda

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Ciencia de Datos y ML

Simplifies genomic data processing by providing a Pythonic interface for reading, writing, and manipulating SAM, BAM, CRAM, and VCF files.

Acerca de

Pysam is a specialized Claude Code skill designed for bioinformaticians and researchers to streamline the analysis of high-throughput sequencing data. It bridges Python workflows with the powerful htslib library, allowing for efficient querying of indexed genomic files, pileup analysis for coverage depth, and the manipulation of variant call formats. Whether you're building NGS pipelines, performing variant annotation, or conducting quality control on large-scale genomic datasets, this skill provides the necessary patterns and best practices to handle complex file formats with precision and high performance.

Características Principales

16 GitHub stars
Advanced pileup analysis for calculating per-base coverage and depth statistics
Comprehensive read/write support for SAM, BAM, CRAM, and VCF/BCF files
Integrated access to samtools and bcftools command-line utilities within Python
Efficient genomic region querying using index files like BAI, CRAI, and TBI
Reference sequence extraction from FASTA and raw data processing from FASTQ

Casos de Uso

Calculating read depth and genomic coverage for clinical variant validation
Developing Next-Generation Sequencing (NGS) data processing and QC pipelines
Filtering and annotating VCF variant files for population genetics research

Acerca de

Características Principales

16 GitHub stars
Advanced pileup analysis for calculating per-base coverage and depth statistics
Comprehensive read/write support for SAM, BAM, CRAM, and VCF/BCF files
Integrated access to samtools and bcftools command-line utilities within Python
Efficient genomic region querying using index files like BAI, CRAI, and TBI
Reference sequence extraction from FASTA and raw data processing from FASTQ

Casos de Uso

Calculating read depth and genomic coverage for clinical variant validation
Developing Next-Generation Sequencing (NGS) data processing and QC pipelines
Filtering and annotating VCF variant files for population genetics research