bisnake2001/2.BAM-filtration
2.BAM-filtration/SKILL.md
--- name: BAM-filtration description: Performs data cleaning and removal operations. This skill takes a raw BAM and creates a new, "clean" BAM file by actively removing artifacts: mitochondrial reads, blacklisted regions, PCR duplicates, and unmapped reads. Use this skill to "clean," "filter," or "remove bad reads" from a dataset. This is a prerequisite step before peak calling. Do NOT use this skill if you only want to view statistics without modifying the file. --- # BAM Filtration for ChIP-s
$ install --global
skillsauthnpx skillsauth add bisnake2001/chromskills 2.BAM-filtrationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- BAM-filtration
- description:
- Performs data cleaning and removal operations. This skill takes a raw BAM and creates a new, "clean" BAM file by actively removing artifacts: mitochondrial reads, blacklisted regions, PCR duplicates, and unmapped reads. Use this skill to "clean," "filter," or "remove bad reads" from a dataset. This is a prerequisite step before peak calling. Do NOT use this skill if you only want to view statistics without modifying the file.
BAM Filtration for ChIP-seq / ATAC-seq
Overview
Main steps include:
- Check the availability of blacklist file in current directory. Always prompt user whether to filter blacklist if blacklist files are missing. if the user need to filter blacklist file, then prompt user for the path of blacklist file.
- Initialize the project directory and create the required directory.
- Refer to the Inputs & Outputs section to check inputs and build the output architecture. All the output file should located in
${proj_dir}in Step 0. - Discover input BAMs in the current directory (or those matching a target token), and only select BAMs that are already coordinate-sorted and contain read group (RG) information.
- Perform the filtration task with tools.
When to use this skill
- Use this skill to "clean," "filter," or "remove bad reads" from a dataset
- This is a prerequisite step before peak calling.
- Do NOT use this skill if you only want to view statistics without modifying the file.
Inputs & Outputs
Inputs
${sample}.bam # BAMs that are already coordinate-sorted and contain read group (RG) information
Outputs
all_bam_filtration/
filtered_bam/
${sample}.filtered.bam
${sample}.filtered.bam.bai
temp/
... # intermediate files
Decision Tree
Step 0: Initialize Project
Call:
mcp__project-init-tools__project_init
with:
sample: alltask: bam_filtration
The tool will:
- Create
${sample}_bam_filtrationdirectory. - Return the full path of the
${sample}_bam_filtrationdirectory, which will be used as${proj_dir}.
Step 1: Filter BAM files
Call:
- mcp__qc-tools__bam_artifacts
with:
bam_file: BAMs that are already coordinate-sorted and contain read group (RG) informationoutput_bam: ${proj_dir}/filtered_bam/${sample}.filtered.bamtemp_dir: ${proj_dir}/temp/blacklist_bed: Path of the blacklist file
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