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pysampysam 生物数据

Agent Skill

pysam 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pysam(pysam 生物数据)
来源仓库:https://github.com/k-dense-ai/scientific-agent-skills
仓库路径:skills/pysam
安装命令:
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill pysam
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill pysam

简介

pysam 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。

  • 适用于前端设计相关项目协作、代码审查或生物序列分析工具开发场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 该技能属于前端设计类工具,当前无官方背书或稳定性结论,需用户自行评估适用性。

SKILL.md

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

uv pip install pysam

Basic Examples

Read alignment file:

import pysam

# Open BAM file and fetch reads in region
samfile = pysam.AlignmentFile("example.bam", "rb")
for read in samfile.fetch("chr1", 1000, 2000):
    print(f"{read.query_name}: {read.reference_start}")
samfile.close()

Read variant file:

# Open VCF file and iterate variants
vcf = pysam.VariantFile("variants.vcf")
for variant in vcf:
    print(f"{variant.chrom}:{variant.pos} {variant.ref}>{variant.alts}")
vcf.close()

Query reference sequence:

# Open FASTA and extract sequence
fasta = pysam.FastaFile("reference.fasta")
sequence = fasta.fetch("chr1", 1000, 2000)
print(sequence)
fasta.close()

Core Capabilities

1. Alignment File Operations (SAM/BAM/CRAM)

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)
  • Coverage analysis (per-base coverage, low coverage detection)
  • Variant analysis (annotation, filtering by read support)
  • Sequence extraction (variant contexts, gene sequences)
  • Read filtering and subsetting
  • Integration patterns (BAM+VCF, VCF+BED, etc.)
  • Performance optimization for complex workflows

Key Concepts

Coordinate Systems

Critical: Pysam uses 0-based, half-open coordinates (Python convention):

  • Start positions are 0-based (first base is position 0)
  • End positions are exclusive (not included in the range)
  • Region 1000-2000 includes bases 1000-1999 (1000 bases total)

Exception: Region strings in fetch() follow samtools convention (1-based):

samfile.fetch("chr1", 999, 2000)      # 0-based: positions 999-1999
samfile.fetch("chr1:1000-2000")       # 1-based string: positions 1000-2000

VCF files: Use 1-based coordinates in the file format, but VariantRecord.start is 0-based.

Indexing Requirements

Random access to specific genomic regions requires index files:

  • BAM files: Require .bai index (create with pysam.index())
  • CRAM files: Require .crai index
  • FASTA files: Require .fai index (create with pysam.faidx())
  • VCF.gz files: Require .tbi tabix index (create with pysam.tabix_index())
  • BCF files: Require .csi index

Without an index, use fetch(until_eof=True) for sequential reading.

File Modes

Specify format when opening files:

  • "rb" - Read BAM (binary)
  • "r" - Read SAM (text)
  • "rc" - Read CRAM
  • "wb" - Write BAM
  • "w" - Write SAM
  • "wc" - Write CRAM

Performance Considerations

  1. Always use indexed files for random access operations
  2. Use pileup() for column-wise analysis instead of repeated fetch operations
  3. Use count() for counting instead of iterating and counting manually
  4. Process regions in parallel when analyzing independent genomic regions
  5. Close files explicitly to free resources
  6. Use until_eof=True for sequential processing without index
  7. Avoid multiple iterators unless necessary (use multiple_iterators=True if needed)

Common Pitfalls

  1. Coordinate confusion: Remember 0-based vs 1-based systems in different contexts
  2. Missing indices: Many operations require index files—create them first
  3. Partial overlaps: fetch() returns reads overlapping region boundaries, not just those fully contained
  4. Iterator scope: Keep pileup iterator references alive to avoid "PileupProxy accessed after iterator finished" errors
  5. Quality score editing: Cannot modify query_qualities in place after changing query_sequence—create a copy first
  6. Stream limitations: Only stdin/stdout are supported for streaming, not arbitrary Python file objects
  7. Thread safety: While GIL is released during I/O, comprehensive thread-safety hasn't been fully validated

Command-Line Tools

Pysam provides access to samtools and bcftools commands:

# Sort BAM file
pysam.samtools.sort("-o", "sorted.bam", "input.bam")

# Index BAM
pysam.samtools.index("sorted.bam")

# View specific region
pysam.samtools.view("-b", "-o", "region.bam", "input.bam", "chr1:1000-2000")

# BCF tools
pysam.bcftools.view("-O", "z", "-o", "output.vcf.gz", "input.vcf")

Error handling:

try:
    pysam.samtools.sort("-o", "output.bam", "input.bam")
except pysam.SamtoolsError as e:
    print(f"Error: {e}")

Resources

references/

Detailed documentation for each major capability:

  • alignment_files.md - Complete guide to SAM/BAM/CRAM operations, including AlignmentFile class, AlignedSegment attributes, fetch operations, pileup analysis, and writing alignments
  • variant_files.md - Complete guide to VCF/BCF operations, including VariantFile class, VariantRecord attributes, genotype handling, INFO/FORMAT fields, and multi-sample operations
  • sequence_files.md - Complete guide to FASTA/FASTQ operations, including FastaFile and FastxFile classes, sequence extraction, quality score handling, and tabix-indexed file access
  • common_workflows.md - Practical examples of integrated bioinformatics workflows combining multiple file types, including quality control, coverage analysis, variant validation, and sequence extraction

Getting Help

For detailed information on specific operations, refer to the appropriate reference document:

  • Working with BAM files or calculating coverage → alignment_files.md
  • Analyzing variants or genotypes → variant_files.md
  • Extracting sequences or processing FASTQ → sequence_files.md
  • Complex workflows integrating multiple file types → common_workflows.md

Official documentation: https://pysam.readthedocs.io/

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