Generate publication-ready IGV screenshots from BAM files and region definitions.
npx skills add https://github.com/sahuno/llm_configs --skill igv-screenshots
Please help me install this Agent Skill. Skill: igv-screenshots Source: https://github.com/sahuno/llm_configs/tree/main/claude/skills/igv-screenshots Command: npx skills add https://github.com/sahuno/llm_configs --skill igv-screenshots
Generating consistent, publication-quality IGV screenshots from BAM files and region definitions can be tedious and error-prone; this skill automates the process to produce reliable visuals quickly.
Run the IGV screenshot workflow by providing BAMs and a regions file; outputs are saved in an organized directory structured as IGV_{genome}_{description}.
High-intent search queries and answers about installing and using this skill.
You can automate IGV screenshots by providing indexed BAM files, a regions file (BED or text), and a genome specification. The workflow outputs publication-ready visuals organized in an IGV_{genome}_{description} directory.
Yes, the workflow supports multi-sample comparisons across genomic regions. You provide multiple BAM files with indices, and it generates comparative publication-quality IGV screenshots for the specified regions.
Yes, the workflow supports methylation coloring for ONT and PacBio reads alongside haplotype visualization options. These features enable specialized tracking of epigenetic modifications and phased variants directly in the screenshots.
You need indexed BAM files, a regions file (BED or text), a genome specification, and an IGV or igver container via Singularity or Docker. Optional configurations allow customizing colors and display settings for the output visuals.
Using an automated containerized workflow ensures consistent, publication-ready IGV visuals from BAM files and region definitions. This approach eliminates manual screenshot errors and standardizes output across multiple samples and genomic regions.
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