BioSkills bio-epitranscriptomics-m6a-peak-calling

Call m6A peaks from MeRIP-seq IP vs input comparisons. Use when identifying m6A modification sites from methylated RNA immunoprecipitation data.

install

source · Clone the upstream repo

git clone https://github.com/GPTomics/bioSkills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/GPTomics/bioSkills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/epitranscriptomics/m6a-peak-calling" ~/.claude/skills/gptomics-bioskills-bio-epitranscriptomics-m6a-peak-calling && rm -rf "$T"

manifest: epitranscriptomics/m6a-peak-calling/SKILL.md

source content

Version Compatibility

Reference examples tested with: MACS3 3.0+

Before using code patterns, verify installed versions match. If versions differ:

R:
```
packageVersion('<pkg>')
```
then
```
?function_name
```
to verify parameters
CLI:
```
<tool> --version
```
then
```
<tool> --help
```
to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

m6A Peak Calling

"Call m6A peaks from my MeRIP-seq data" → Identify m6A-modified RNA regions by comparing immunoprecipitated (IP) and input samples using statistical enrichment testing.

R:
```
exomePeak2::exomePeak2()
```
for GC-bias aware peak calling
CLI:
```
macs3 callpeak
```
as an alternative broad peak caller

exomePeak2 (Recommended)

Goal: Identify m6A-enriched regions by comparing IP and input samples with GC-bias correction and replicate-aware statistical testing.

Approach: Provide IP and input BAM files along with a gene annotation to exomePeak2, which models read counts in sliding windows across the transcriptome and calls significant enrichment peaks.

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