Deeptools

What it does

The ovachiever-deeptools skill provides access to DeepTools, a suite of tools for analyzing and interpreting genomic data. It allows AI agents to perform tasks such as calculating differential methylation, performing ATAC-seq peak annotation, and generating heatmaps from genomic datasets. This skill is particularly useful for researchers working with epigenomic data.

When to use it

• Analyzing RNA sequencing (RNA-Seq) data to identify differentially expressed genes between experimental conditions.
• Performing quality control on single-cell ATAC-seq data by identifying and removing low-quality cells.
• Generating heatmaps visualizing genomic regions with significant changes in methylation patterns.
• Annotating peaks identified from ATAC-seq experiments, linking them to known regulatory elements.
• Investigating the impact of genetic variants on gene expression through differential methylation analysis.

Key capabilities

• Differential Methylation Analysis
• ATAC-seq Peak Annotation
• Heatmap Generation
• Quality Control for Single-Cell Data
• Genomic Data Interpretation

Example prompts

• "Run a differential methylation analysis on these bisulfite sequencing reads, comparing group A to group B."
• "Annotate the peaks from this ATAC-seq experiment using the latest gene annotation file."
• “Generate a heatmap showing the average methylation level across each chromosome.”

Tips & gotchas

The skill requires familiarity with genomic data formats (e.g., BAM, BED). Ensure that input files are properly formatted and indexed for optimal performance.