Bio epitranscriptomics m6a peak calling
Skill FridrichMethod/awesome-skills/skills/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.From its SKILL.md
npx -y skills add FridrichMethod/awesome-skills --skill bio-epitranscriptomics-m6a-peak-callingAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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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
What ships with it: 3 files
3.3 KB alongside SKILL.md, 1 of them executable
examples/
- exomepeak2_peaks.R967 B
- macs3_peaks.shruns858 B
- usage-guide.md1.5 KB