BAM-filtration
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.
Best use case
BAM-filtration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using BAM-filtration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/2-bam-filtration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How BAM-filtration Compares
| Feature / Agent | BAM-filtration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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
```bash
${sample}.bam # BAMs that are already coordinate-sorted and contain read group (RG) information
```
### Outputs
```bash
all_bam_filtration/
filtered_bam/
${sample}.filtered.bam
${sample}.filtered.bam.bai
temp/
... # intermediate files
```
---
## Decision Tree
### Step 0: Initialize Project
Call:
- `mcp__project-init-tools__project_init`
with:
- `sample`: all
- `task`: bam_filtration
The tool will:
- Create `${sample}_bam_filtration` directory.
- Return the full path of the `${sample}_bam_filtration` directory, which will be used as `${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) information
- `output_bam`: ${proj_dir}/filtered_bam/${sample}.filtered.bam
- `temp_dir`: ${proj_dir}/temp/
- `blacklist_bed`: Path of the blacklist fileRelated Skills
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