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/bio-epitranscriptomics-m6a-peak-calling

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openclaw-medical-skills
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Install
$ npx -y skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-epitranscriptomics-m6a-peak-calling --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/bio-epitranscriptomics-m6a-peak-calling

Context preview

The summary Claude sees to decide when to auto-load this skill.

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SKILL.md

bio-epitranscriptomics-m6a-peak-calling.SKILL.md

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COPYRIGHT NOTICE

This file is part of the "Universal Biomedical Skills" project.

Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>

All Rights Reserved.

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This code is proprietary and confidential.

Unauthorized copying of this file, via any medium is strictly prohibited.

#

Provenance: Authenticated by MD BABU MIA

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--- name: bio-epitranscriptomics-m6a-peak-calling description: Call m6A peaks from MeRIP-seq IP vs input comparisons. Use when identifying m6A modification sites from methylated RNA immunoprecipitation data. tool_type: mixed primary_tool: exomePeak2 measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

---

m6A Peak Calling

exomePeak2 (Recommended)

library(exomePeak2)

# Peak calling with biological replicates
result <- exomePeak2(
    bam_ip = c('IP_rep1.bam', 'IP_rep2.bam'),
    bam_input = c('Input_rep1.bam', 'Input_rep2.bam'),
    gff = 'genes.gtf',
    genome = 'hg38',
    paired_end = TRUE
)

# Export peaks
exportResults(result, format = 'BED')

MACS3 Alternative

# Call peaks treating input as control
macs3 callpeak \
    -t IP_rep1.bam IP_rep2.bam \
    -c Input_rep1.bam Input_rep2.bam \
    -f BAMPE \
    -g hs \
    -n m6a_peaks \
    --nomodel \
    --extsize 150 \
    -q 0.05

MeTPeak

library(MeTPeak)

# GTF-aware peak calling
metpeak(
    IP_BAM = c('IP_rep1.bam', 'IP_rep2.bam'),
    INPUT_BAM = c('Input_rep1.bam', 'Input_rep2.bam'),
    GENE_ANNO_GTF = 'genes.gtf',
    OUTPUT_DIR = 'metpeak_output'
)

Peak Filtering

# Filter by fold enrichment and q-value
# FC > 2, q < 0.05 typical thresholds
awk '$7 > 2 && $9 < 0.05' peaks.xls > filtered_peaks.bed

Related Skills

  • merip-preprocessing - Prepare data for peak calling
  • m6a-differential - Compare peaks between conditions
  • chip-seq/peak-calling - Similar concepts

<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

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The largest open-source medical AI skill library for OpenClaw.

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Repo: FreedomIntelligence/OpenClaw-Medical-Skills