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Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.
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LanguagePython
LicenseMIT
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</> SKILL.md
pysam.SKILL.md
---name: pysam
description: Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.
license: MIT license
metadata: {"version": "1.0", "skill-author": "K-Dense Inc."}
---# Pysam
## Overview
Pysam is a Python module for reading, manipulating, and writing genomic datasets. Read/write SAM/BAM/CRAM alignment files, VCF/BCF variant files, and FASTA/FASTQ sequences with a Pythonic interface to htslib. Query tabix-indexed files, perform pileup analysis for coverage, and execute samtools/bcftools commands.
## When to Use This Skill
This skill should be used when:
- Working with sequencing alignment files (BAM/CRAM)
- Analyzing genetic variants (VCF/BCF)
- Extracting reference sequences or gene regions
- Processing raw sequencing data (FASTQ)
- Calculating coverage or read depth
- Implementing bioinformatics analysis pipelines
- Quality control of sequencing data
- Variant calling and annotation workflows
## Quick Start
### Installation
```bash
uv pip install pysam
```
### Basic Examples
Use the `AlignmentFile` class to work with aligned sequencing reads. This is appropriate for analyzing mapping results, calculating coverage, extracting reads, or quality control.
**Common operations:**
- Open and read BAM/SAM/CRAM files
- Fetch reads from specific genomic regions
- Filter reads by mapping quality, flags, or other criteria
- Write filtered or modified alignments
- Calculate coverage statistics
- Perform pileup analysis (base-by-base coverage)
- Access read sequences, quality scores, and alignment information
**Reference:** See `references/alignment_files.md` for detailed documentation on:
- Opening and reading alignment files
- AlignedSegment attributes and methods
- Region-based fetching with `fetch()`
- Pileup analysis for coverage
- Writing and creating BAM files
- Coordinate systems and indexing
- Performance optimization tips
### 2. Variant File Operations (VCF/BCF)
Use the `VariantFile` class to work with genetic variants from variant calling pipelines. This is appropriate for variant analysis, filtering, annotation, or population genetics.
**Common operations:**
- Read and write VCF/BCF files
- Query variants in specific regions
- Access variant information (position, alleles, quality)
- Extract genotype data for samples
- Filter variants by quality, allele frequency, or other criteria
- Annotate variants with additional information
- Subset samples or regions
**Reference:** See `references/variant_files.md` for detailed documentation on:
- Opening and reading variant files
- VariantRecord attributes and methods
- Accessing INFO and FORMAT fields
- Working with genotypes and samples
- Creating and writing VCF files
- Filtering and subsetting variants
- Multi-sample VCF operations
### 3. Sequence File Operations (FASTA/FASTQ)
Use `FastaFile` for random access to reference sequences and `FastxFile` for reading raw sequencing data. This is appropriate for extracting gene sequences, validating variants against reference, or processing raw reads.
**Common operations:**
- Query reference sequences by genomic coordinates
- Extract sequences for genes or regions of interest
- Read FASTQ files with quality scores
- Validate variant reference alleles
- Calculate sequence statistics
- Filter reads by quality or length
- Convert between FASTA and FASTQ formats
**Reference:** See `references/sequence_files.md` for detailed documentation on:
- FASTA file access and indexing
- Extracting sequences by region
- Handling reverse complement for genes
- Reading FASTQ files sequentially
- Quality score conversion and filtering
- Working with tabix-indexed files (BED, GTF, GFF)
- Common sequence processing patterns
### 4. Integrated Bioinformatics Workflows
Pysam excels at integrating multiple file types for comprehensive genomic analyses. Common workflows combine alignment files, variant files, and reference sequences.
**Common workflows:**
- Calculate coverage statistics for specific regions
- Validate variants against aligned reads
- Annotate variants with coverage information
- Extract sequences around variant positions
- Filter alignments or variants based on multiple criteria
- Generate coverage tracks for visualization
- Quality control across multiple data types
**Reference:** See `references/common_workflows.md` for detailed examples of:
- Quality control workflows (BAM statistics, reference consistency)
