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Get Started Free →Call m6A peaks from MeRIP-seq IP vs input comparisons. Use when identifying m6A modification sites from methylated RNA immunoprecipitation data.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -27% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -8% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -7% | 0% |
| case-11 | ✗→✓ | ▲ Improved | -28% | 0% |
| case-17 | ✗→✓ | ▲ Improved | -36% | 0% |
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rlibrary(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')
bash# 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
rlibrary(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' )
bash# 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
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