alterlab-pysam

alterlab-pysam is a skill for Claude Code from AlterLab-IEU/AlterLab-Academic-Skills. It costs 98 tokens per session (2,501 once invoked), scanned A, a copy of pysam, MIT.

A Python tool for reading and writing common genomics files, including SAM, BAM, and CRAM alignments, VCF and BCF variant files, and FASTA and FASTQ sequences. It also supports indexed region queries and coverage pileups.

In plain words
What is it for?
Use it in sequencing pipelines to extract reads or reference regions, filter alignments and variants, calculate coverage, inspect raw reads, and support quality-control or variant-calling workflows.
Why use it?
It lets Python programs work with large sequencing files and established command-line genomics tools without manually parsing each file format.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the alterlab-bioinformatics plugin — 38 skills shipped together

Good fit Use it in sequencing pipelines to extract reads or reference regions, filter alignments and variants, calculate coverage, inspect raw reads, and support quality-control or variant-calling workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alterlab-ieu/alterlab-academic-skills/alterlab-pysam
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-pysam
Clone the repo
git clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-Skills

Made for: Claude Code.

Or install alterlab-bioinformatics, the plugin that ships this one along with the rest of its 38 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for alterlab-pysam

README.md
[![agentmods](https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pysam/github.svg)](https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pysam)
Your own site
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pysam"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pysam/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for alterlab-pysam

Your own site · 80×15
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pysam"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-pysam.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 98 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,501 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 98% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00098 $0.02501
Opus 5 $0.00049 $0.01251
Sonnet 5 $0.00020 $0.00500
Haiku 4.5 $0.00010 $0.00250

Measured 12d ago against content hash dc8f2d5d818c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

alterlab-pysam scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

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

This is a copy

98% identical to pysam — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/bioinformatics/alterlab-pysam/SKILL.md · 269 lines

How it starts

The opening of the file, as written. The whole thing — 269 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 269 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 269 lines · 98 tokens per session scan A dc8f2d5d818c

Subscribe to this mod's changes

alterlab-pysam is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 7d ago), licensed MIT. It adds 98 tokens to every session and 2,501 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 98% identical to pysam, differing in 16 lines, and is treated as a copy.

Related

Other skills, from other repositories

fluidsim

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC…

Lord1Egypt/scientific-agent-toolkit · 69 tokens

astropy

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve…

Lord1Egypt/scientific-agent-toolkit · 84 tokens

simpy

Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.

Lord1Egypt/scientific-agent-toolkit · 56 tokens

biopython

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use…

Lord1Egypt/scientific-agent-toolkit · 76 tokens

scanpy

Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use…

Lord1Egypt/scientific-agent-toolkit · 68 tokens

datamol

Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters…

Lord1Egypt/scientific-agent-toolkit · 67 tokens