Run the DROP nf-core pipeline to detect aberrant expression, splicing, and mono-allelic expression from RNA sequencing data.
npx skills add https://github.com/danilomonge/nf-claw --skill drop
Please help me install this Agent Skill. Skill: drop Source: https://github.com/danilomonge/nf-claw/tree/main/pipelines/drop Command: npx skills add https://github.com/danilomonge/nf-claw --skill drop
This Skill helps you run the DROP nf-core pipeline without manual schema hunting, so you can analyze RNA sequencing data for aberrant expression, aberrant splicing, and mono-allelic expression with the correct parameters and outputs.
Ask the assistant to run the DROP pipeline on your samplesheet with the right genome, output directory, and sequencing input type for your dataset.
High-intent search queries and answers about installing and using this skill.
You can detect aberrant expression and splicing by running an nf-core pipeline that processes RNA sequencing inputs like BAM or CRAM files and gene counts to identify expression and splicing outliers across genome-specific workflows.
Monoallelic expression detection identifies allele-specific expression outliers from RNA sequencing data. It works by running an nf-core pipeline that processes BAM or CRAM inputs and gene counts to pinpoint aberrant allele-specific signals.
Yes, you can use BAM or CRAM files to detect RNA outliers with Nextflow. The pipeline supports samplesheet-driven runs that accept raw BAM or CRAM inputs, gene counts with annotations, or splice count directories.
To run an RNA-seq outlier detection pipeline, you need validated input files such as raw BAM or CRAM, gene counts, and splice counts. You also must specify the output directory and genome parameters for your workflow.
You configure reproducible RNA analysis by applying validated required inputs, optional analysis groups, genome settings, and release-specific flags. This ensures your runs remain schema-compliant and reproducible across different sequencing input modes.
zongtingweiQuantify gene and transcript abundances from RNA-seq reads using salmon, kallisto, or featureCounts.
TianGzlabAssess library size, gene detection, and sample correlation in bulk RNA-seq count matrices.
EpiphyticRun nf-core Nextflow pipelines for RNA-seq, variant, and ATAC-seq analyses.
Lord1EgyptPerform RNA velocity analysis on single-cell RNA-seq AnnData objects.
