What coordinate system does Pysam use?

Pysam follows the Python convention of 0-based, half-open coordinates for internal operations, though it supports 1-based region strings when using the fetch() method.

Is Pysam suitable for processing large sequencing datasets?

Absolutely. Pysam is built on htslib, which is designed for high-performance processing of massive genomic files through efficient streaming and indexing.

Does this skill require pre-existing index files?

Yes, for random access to specific genomic regions, Pysam requires standard index files such as .bai for BAM, .fai for FASTA, and .tbi for VCF files.

Can I run samtools commands directly through Pysam?

Yes, Pysam provides a wrapper that allows you to execute samtools and bcftools commands as Python functions, including sort, index, and view.

Pysam Genomic Toolkit

Name: Pysam Genomic Toolkit
Author: K-Dense-AI

byK-Dense-AI

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3,719

Data Science & ML

Reads, manipulates, and writes genomic datasets including BAM, VCF, and FASTA files using a Pythonic interface to htslib.

About

Pysam is a specialized skill for bioinformaticians and developers working with Next-Generation Sequencing (NGS) data. It provides high-performance access to genomic file formats like SAM/BAM/CRAM for alignments, VCF/BCF for variants, and FASTA/FASTQ for sequences. By wrapping the htslib C-library, it allows Claude to perform complex tasks such as region-based fetching, pileup analysis for depth calculation, and the execution of samtools or bcftools commands directly within Python scripts, making it ideal for building robust genomic analysis pipelines and quality control workflows.

Key Features

Advanced variant manipulation for VCF and BCF files including genotype access.
Random access to indexed FASTA reference sequences and FASTQ processing.
Comprehensive read/write support for SAM, BAM, and CRAM alignment files.
Direct integration with samtools and bcftools command-line utilities.
Per-base coverage analysis using htslib-powered pileup engines.
3,719 GitHub stars

Use Cases

Performing quality control and coverage statistics on large-scale sequencing datasets.
Extracting specific genomic regions or gene sequences for downstream biological analysis.
Developing automated NGS pipelines for alignment processing and variant calling.

About

Key Features

Advanced variant manipulation for VCF and BCF files including genotype access.
Random access to indexed FASTA reference sequences and FASTQ processing.
Comprehensive read/write support for SAM, BAM, and CRAM alignment files.
Direct integration with samtools and bcftools command-line utilities.
Per-base coverage analysis using htslib-powered pileup engines.
3,719 GitHub stars

Use Cases

Performing quality control and coverage statistics on large-scale sequencing datasets.
Extracting specific genomic regions or gene sequences for downstream biological analysis.
Developing automated NGS pipelines for alignment processing and variant calling.