6.track-generation/SKILL.md
This skill generates normalized BigWig (.bw) tracks (and/or fold-change tracks) from BAM files for ATAC-seq and ChIP-seq visualization. It handles normalization (RPM or fold-change) and Tn5 offset correction automatically. What's more, this skill can help user visualize the signal profiles around TSS or target regions. Use this skill when you have filtered and generated the clean BAM file (e.g. `*.filtered.bam`).
npx skillsauth add bisnake2001/chromskills track-generationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill converts filtered BAM files into normalized signal tracks (BigWig) for genome browser visualization.
It supports both ATAC-seq and ChIP-seq datasets, automatically detecting genome assembly and chromosome size files.
Main steps include:
${proj_dir} in Step 0.*.filtered.bam) if available.Call:
mcp__project-init-tools__project_initwith:
sample: alltask: track_generationThe tool will:
${sample}_track_generation directory.${sample}_track_generation directory, which will be used as ${proj_dir}.Call:
mcp__bw-tools__generate_chrom_sizes
with:bam_file: Path for the BAM file for generating bigWig Tracksoutput_path: ${proj_dir}/temp/${sample}.chrom.sizesCall:
mcp__bw_tools__calculate_scaling_factor
with:
bam_file: Path for the BAM file for generating bigWig TracksThis step will store result as variable ${scale_factor}
Call:
mcp__bw_tools__bam_to_bigwig
with:
bam_file: ${bam_file}
chrom_sizes: ${proj_dir}/temp/${sample}.chrom.sizes (from Step 2)
output_bw: ${proj_dir}/tracks/${sample_name}.RPM.bw
scale_factor: ${scale_factor}
shift_tn5: True
temp_dir: ${proj_dir}/temp
(Option 2) For ChIP-seq data:
Do Not Apply the standard Tn5 shift by setting shift_tn5 as False
Call:
mcp__bw_tools__visualize_signal_profile
with:
regions_bed: GTF (for gene tss) or BED file (for target regions), always query user for this file if not provided.
signal_files: Input BigWig signal files.
output_prefix: Output prefix for matrix/plots.
reference_point: use TSS for genes, and center for target regions.
upstream: Upstream distance (bp).
downstream: Downstream distance (bp).development
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development
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data-ai
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devops
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