magmap

Run the nf-core/magmap pipeline for validated read mapping against large genome collections.

1|Updated Jun 19, 2026

Search Tags:#bioinformatics #nf-core #nextflow #metagenomics #samplesheet #genome mapping #metatranscriptomics

Ready to run

npx skills add https://github.com/danilomonge/nf-claw --skill magmap

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: magmap
Source: https://github.com/danilomonge/nf-claw/tree/main/pipelines/magmap
Command: npx skills add https://github.com/danilomonge/nf-claw --skill magmap

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the guesswork from running nf-core/magmap so an AI can launch a valid, reproducible read-mapping analysis without inventing flags or missing required inputs.

Core Features & Use Cases

Validated pipeline execution: Uses the pinned magmap release metadata to keep commands, parameters, and provenance aligned with the exact pipeline version.
Research-ready workflows: Supports metagenomic and metatranscriptomic mapping, quality control, trimming, genome selection, and feature quantification for large genome collections.
Reliable outputs: Produces organized results, run metadata, and MultiQC summaries that can be reused in downstream analysis or reporting.

Quick Start

Ask the assistant to run nf-core/magmap on your samplesheet with an output directory and a Docker profile.

Frequently Asked Questions about magmap

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I map metagenomic sequencing reads against large genome collections?▼

You can map reads against large genome collections by running the nf-core/magmap pipeline, which enforces required inputs, validates samplesheets, and executes reproducible read-mapping with optional trimming and QC.

How do I validate a samplesheet for nf-core metagenomics pipelines before running?▼

Samplesheet validation for nf-core metagenomics pipelines is enforced automatically during execution, using schema-validated pipeline metadata to prevent invalid flags and ensure inputs align with the pinned release.

Can I run metatranscriptomics read mapping and feature quantification with Nextflow?▼

Yes, you can run metatranscriptomics read mapping and feature quantification with Nextflow by executing the nf-core/magmap pipeline, which supports these workflows alongside genome selection and quality control.

Do I need Docker to run nf-core genome mapping pipelines?▼

A Docker profile is supported for running nf-core genome mapping pipelines, ensuring reproducible execution and organized results that include run metadata and MultiQC summaries for downstream analysis.

What is the best way to ensure reproducible Nextflow pipeline execution for metagenomic workflows?▼

The best way to ensure reproducible Nextflow pipeline execution is to use release pinning and schema-validated metadata, which keeps commands, parameters, and provenance aligned with the exact pipeline version.

Are there limitations when overriding Nextflow engine parameters for nf-core pipelines?▼

While Nextflow engine overrides are supported, invalid flags are prevented by schema-validated pipeline metadata, meaning any overrides must conform to the pinned magmap release constraints to avoid execution failures.