Convert BAM files to normalized bigWig tracks and generate quality control metrics.
npx skills add https://github.com/Sologa/codex-pipeline --skill deeptools-sologa
Please help me install this Agent Skill. Skill: deeptools Source: https://github.com/Sologa/codex-pipeline/tree/main/.codex/skills/deeptools Command: npx skills add https://github.com/Sologa/codex-pipeline --skill deeptools-sologa
This Skill simplifies complex Next-Generation Sequencing (NGS) data analysis, enabling researchers to quickly process, visualize, and interpret genomic data without deep command-line expertise.
Use the deeptools skill to generate a quality control heatmap for your ChIP-seq BAM files.
High-intent search queries and answers about installing and using this skill.
To convert BAM files to normalized bigWig tracks for ChIP-seq visualization, you can use this Skill's data conversion scripts to process raw BAM files and output normalized coverage tracks for genomic visualization.
Generating quality control heatmaps for NGS data involves assessing sample correlation and enrichment metrics. This Skill computes quality control metrics and visualizes signal enrichment around genomic features like TSS or peaks.
You can analyze RNA-seq and ATAC-seq workflows without deep command-line expertise by using this Skill's specialized scripts and reference documentation to simplify complex NGS data processing and visualization.
To visualize ChIP-seq signal enrichment around known peak regions, this Skill generates profile plots and heatmaps around genomic features, allowing you to compare signal between treated and control samples.
Yes, this NGS data analysis toolkit provides reference documentation for effective genome sizes and normalization, supporting accurate calculation of quality control metrics across ChIP-seq and ATAC-seq workflows.
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ovachieverConvert BAM alignments into normalized coverage tracks and generate QC metrics.
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