Run the nf-core/callingcards pipeline for Calling Cards sequencing data.
npx skills add https://github.com/danilomonge/nf-claw --skill callingcards
Please help me install this Agent Skill. Skill: callingcards Source: https://github.com/danilomonge/nf-claw/tree/main/pipelines/callingcards Command: npx skills add https://github.com/danilomonge/nf-claw --skill callingcards
This Skill removes the guesswork from running the nf-core/callingcards workflow so you can process Calling Cards sequencing data with the correct inputs, parameters, and outputs every time.
Tell the assistant to run the callingcards skill on your samplesheet, choose the organism type, and write the results to your desired output directory.
High-intent search queries and answers about installing and using this skill.
You run the nf-core callingcards pipeline by providing a structured samplesheet, specifying the organism type, and setting an output directory. The workflow handles read processing, insertion counting, and quality control reporting automatically.
Yes, the callingcards pipeline supports both mammalian and yeast experiments. You must supply the appropriate genome or annotation reference inputs for alignment and downstream insertion counting analysis.
The samplesheet must tie each sample to its corresponding sequencing reads and barcode details. This structured input drives the nf-core pipeline execution for accurate insertion counting and downstream QC.
Yes, the callingcards pipeline uses nf-schema and Nextflow to enforce validated parameters for datatype, input, and output directory settings. This ensures reproducible execution and reliable quality control reporting.
The callingcards pipeline produces organized results, pipeline metadata, and MultiQC summaries. These outputs allow you to review insertion counting results and share quality control reports across experiments.
Without the correct genome or annotation reference inputs, the callingcards pipeline cannot perform accurate alignment or insertion counting. Validated parameters for datatype and reference settings are required for successful execution.
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