replicates-incorporation
This skill manages experimental reproducibility, pooling, and consensus strategies. This skill operates in two distinct modes based on the input state. (1) Pre-Peak Calling (BAM Mode): It merges all BAMs, generate the merge BAM file to prepare for track generation and (if provided with >3 biological replicates) splits them into 2 balanced "pseudo-replicates" to prepare for peak calling. (2) Post-Peak Calling (Peak Mode): If provided with peak files (only support two replicates, derived from either 2 true replicates or 2 pseudo-replicates), it performs IDR (Irreproducible Discovery Rate) analysis, filters non-reproducible peaks, and generates a final "conservative" or "optimal" consensus peak set. Trigger this skill when you need to handle more than two replicates (creating pseudo-reps) OR when you need to merge peak lists.
Best use case
replicates-incorporation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
This skill manages experimental reproducibility, pooling, and consensus strategies. This skill operates in two distinct modes based on the input state. (1) Pre-Peak Calling (BAM Mode): It merges all BAMs, generate the merge BAM file to prepare for track generation and (if provided with >3 biological replicates) splits them into 2 balanced "pseudo-replicates" to prepare for peak calling. (2) Post-Peak Calling (Peak Mode): If provided with peak files (only support two replicates, derived from either 2 true replicates or 2 pseudo-replicates), it performs IDR (Irreproducible Discovery Rate) analysis, filters non-reproducible peaks, and generates a final "conservative" or "optimal" consensus peak set. Trigger this skill when you need to handle more than two replicates (creating pseudo-reps) OR when you need to merge peak lists.
Teams using replicates-incorporation 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/7-replicates-incorporation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How replicates-incorporation Compares
| Feature / Agent | replicates-incorporation | 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?
This skill manages experimental reproducibility, pooling, and consensus strategies. This skill operates in two distinct modes based on the input state. (1) Pre-Peak Calling (BAM Mode): It merges all BAMs, generate the merge BAM file to prepare for track generation and (if provided with >3 biological replicates) splits them into 2 balanced "pseudo-replicates" to prepare for peak calling. (2) Post-Peak Calling (Peak Mode): If provided with peak files (only support two replicates, derived from either 2 true replicates or 2 pseudo-replicates), it performs IDR (Irreproducible Discovery Rate) analysis, filters non-reproducible peaks, and generates a final "conservative" or "optimal" consensus peak set. Trigger this skill when you need to handle more than two replicates (creating pseudo-reps) OR when you need to merge peak lists.
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
# Replicates Incorporation Skill
## Overview
This skill provides two modes for replicates incorporation:
- Refer to the **Inputs & Outputs** section to check inputs and build the output architecture. All the output file should located in `${proj_dir}` in Step 0.
- Always use filtered BAM file (`*.filtered.bam`) if available.
- Always prompt user for whether generate psedo-replicates if more then 2 replicates.
- Pre-Peak Calling (BAM Mode): If provided with >2 biological replicates, it merges all BAMs, generate the merge BAM file to prepare for track generation and splits them into 2 balanced "pseudo-replicates" to prepare for peak calling only if user required.
- Post-Peak Calling (Peak Mode): If provided with peak files (only support two replicates, derived from either 2 true replicates or 2 pseudo-replicates), it performs IDR (Irreproducible Discovery Rate) analysis, filters non-reproducible peaks, and generates a final "conservative" or "optimal" consensus peak set
---
## Decision Tree
### Step 0: Initialize Project
Call:
- `mcp__project-init-tools__project_init`
with:
- `sample`: all
- `task`: rep_merge
The tool will:
- Create `all_rep_merge` directory.
- Return the full path of the `all_rep_merge` directory, which will be used as `${proj_dir}`
### Pre-Peak Calling (BAM Mode)
Call:
- `mcp__bw_tools__pool_bams`
with:
- `bam_files`: `[${rep1_bam}, ${rep2_bam}, ${rep3_bam}]` (Add as many as needed)
- `output_bam`: `${proj_dir}/temp/${sample}.pooled.bam`
Call: (call this only when more than two replicates are provided and user prompt for generating pseudo replicates)
- `mcp__bw_tools__split_pseudo_replicates`
with:
bam_file: `${proj_dir}/temp/${sample}.pooled.bam`
output_rep1: `${proj_dir}/temp/${sample}.pseudo1.bam`
output_rep2: `${proj_dir}/temp/${sample}.pseudo2.bam`
---
### Post-Peak Calling (Peak Mode)
**A. Narrow Peaks / ATAC (IDR)**
Use this to combine reproducible peaks. You should ideally run IDR on:
1. True Replicates
2. Pseudo-Replicates
Call:
- `mcp__bw_tools__filter_idr_peaks`
with:
- `peak_file_a`: Path to Replicate 1 narrowPeak file.
- `peak_file_b`: Path to Replicate 2 narrowPeak file.
- `output_optimal`: `${proj_dir}/peaks/${sample}.idr.narrowPeaks`
- `output_raw_idr`: `${proj_dir}/temp/${sample}_idr_results.tsv`
- `input_file_type`: narrowPeak
- `rank_measure`: q.value
**B. Broad Peaks (Consensus)**
Call:
- `mcp__bw_tools__merge_consensus_peaks`
with:
`peak_file_a`: Path to Replicate 1 broadPeak file.
`peak_file_b`: Path to Replicate 2 broadPeak file.
`output_peak`: `${proj_dir}/peaks/${sample}.consensus.broadPeaks`
`overlap_fraction`: 0.5
---
## Best Practices
- **Use pooled tracks** for visualization and differential analysis.
- **Keep individual replicate tracks** for QC and reproducibility evaluation.
- **Use IDR ≤ 0.05** for reproducible narrow ChIP-seq peaks and ATAC-seq.
- **Use overlap ≥50% ** for broad histone mark peaks.Related Skills
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