Generate and run nf-core rnaseq workflows from CSV samplesheets.
npx skills add https://github.com/danilomonge/nf-claw --skill rnaseq
Please help me install this Agent Skill. Skill: rnaseq Source: https://github.com/danilomonge/nf-claw/tree/main/pipelines/rnaseq Command: npx skills add https://github.com/danilomonge/nf-claw --skill rnaseq
This Skill turns the complex nf-core rnaseq pipeline into a guided, reliable workflow for RNA sequencing analysis, reducing guesswork around inputs, flags, and release-specific behavior.
Ask the Skill to run an nf-core rnaseq analysis for your samplesheet and output directory, then it will guide the correct parameters for the selected pipeline version.
High-intent search queries and answers about installing and using this skill.
To run nf-core RNA-seq analysis, provide a valid CSV samplesheet and an output directory. The workflow validates parameters against the pinned pipeline release and nf-schema constraints to process FASTQ inputs for alignment, quantification, and QC.
Yes, RNA-seq analysis supports pre-aligned BAM inputs alongside standard FASTQ files. The workflow accommodates both input types within the samplesheet-driven experiment structure, applying appropriate downstream processing for each scenario.
The RNA-seq workflow supports alignment, pseudoalignment, trimming, quality control, quantification, contamination screening, and UMI handling scenarios. Parameter combinations are validated against schema-backed constraints to ensure valid run configurations.
Parameter validation checks inputs against the pinned pipeline release and full nf-schema constraints. This surfaces schema-backed restrictions and allowed values, preventing invalid parameter combinations before executing the RNA-seq analysis.
The nf-core rnaseq workflow generates and runs Nextflow pipelines, requiring a valid CSV samplesheet and output directory. It guides correct parameter selection for the pinned pipeline version to ensure reproducible transcriptomics analysis.
Invalid parameter combinations fail because the workflow enforces schema-backed constraints and allowed values from the pinned nf-core rnaseq release. The guided validation surfaces these restrictions to prevent misconfigured runs before execution.
danilomongeConvert BAM or CRAM inputs into FASTQ outputs for nf-core bamtofastq runs.
zongtingweiNormalize and quality-check bulk RNA-seq count matrices with Python.
giadaf-booshaAutomate sequencing data analysis with nf-core bioinformatics pipelines.
galeepAutomate bulk RNA-seq analysis from quality control to pathway enrichment.
