Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM), MeTPeak (HMM over sliding windows), MACS3/MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody methods cannot resolve, and orthogonal validation (miCLIP/GLORI/m6A-SAC-seq/m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set, reconciling differing peak sets across tools, validating MeRIP peaks against single-base methods, interpreting 5' peaks where m6Am contamination is possible, or recommending a consensus strategy.
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Calls m6A peaks from MeRIP-seq / m6A-seq paired IP-vs-input data using exomePeak2 (transcript-aware, GC-bias-corrected Poisson GLM), MeTPeak (HMM over sliding windows), MACS3/MACS2 with --nomodel --broad --keep-dup all (genome-wide broad alternative), and DRACH motif enrichment via HOMER or ggseqlogo as a sanity check (NOT a filter). Covers BED12 vs narrowPeak output, exonic vs intronic peak handling, multi-tool reconciliation (intersection vs union), the m6A-vs-m6Am ambiguity at 5'UTR peaks that antibody methods cannot resolve, and orthogonal validation (miCLIP/GLORI/m6A-SAC-seq/m6Anet). Use when calling peaks from paired IP/input genome BAMs, choosing exomePeak2 (transcript-aware default) vs MACS3 (broad genomic) vs MeTPeak (HMM-smoothed low-coverage), confirming DRACH enrichment as a sanity check on the peak set, reconciling differing peak sets across tools, validating MeRIP peaks against single-base methods, interpreting 5' peaks where m6Am contamination is possible, or recommending a consensus strategy.
Before using code patterns, verify installed versions match. If versions differ:
R: packageVersion('exomePeak2') then ?exomePeak2 to verify parameters
CLI: macs3 callpeak --help, findMotifsGenome.pl to confirm flags
If R throws unused argument or argument is missing, the exomePeak2 / MeTPeak API may have moved between releases; consult ?exomePeak2 and the installed package's NAMESPACE.
exomePeak2 differential is triggered by populating bam_treated_ip / bam_treated_input alongside the control-arm bam_ip / bam_input (see m6a-differential); there is NO mode= argument. MeTPeak is GitHub-only and unversioned — pin a commit SHA in any reproducible analysis; defaults are WINDOW_WIDTH=50, SLIDING_STEP=50, FRAGMENT_LENGTH=100. MACS3 supersedes MACS2 in development activity but both are widely used; default --keep-dup is 1 in BOTH and MUST be overridden to all for MeRIP. HOMER findMotifsGenome.pl is mature; the -rna flag is the RNA-mode entry.
m6A Peak Calling
"Find m6A sites in my MeRIP data" -> Compare paired IP and input read distributions per transcript window, call windows with statistically significant IP enrichment as peaks, annotate against transcript features (5'UTR / CDS / 3'UTR / stop-codon), and confirm DRACH motif enrichment on the peak set relative to background as a sanity check that the antibody-IP worked. CRITICAL: DRACH is a sanity check on the WHOLE peak set, NOT a filter on individual peaks (filtering by DRACH drops 5-10% of real m6A sites and creates circular validation). Equally critical: peaks within ~50 nt of TSS may be PCIF1 m6Am, not METTL3 m6A — anti-m6A antibodies cross-react.
R: ggseqlogo::ggseqlogo() -- peak-centre 5-mer sequence logo
The Single Most Important Modern Insight -- MeRIP cannot distinguish m6A from m6Am near the 5' end, and DRACH is a sanity check not a filter
Anti-m6A antibodies (Synaptic Systems 202-003, Abcam ab151230, NEB EpiMark E1610, Cell Signaling 56593, Active Motif 61755) cross-react with m6Am — the cap-adjacent N6,2'-O-dimethyladenosine at the +1 nucleotide of capped mRNAs, installed by PCIF1 / CAPAM (Akichika 2019 Science 363:eaav0080; Boulias 2019 Mol Cell 75:631). METTL3 / METTL14 do NOT methylate the cap-adjacent position; PCIF1 does. Peaks within the first ~50 nt of a transcript are ambiguous between m6A and m6Am. METTL3-KO will REMOVE internal m6A peaks but LEAVE the cap m6Am peaks intact, which has caused multiple papers to mis-attribute METTL3-independent peaks to non-canonical writers when they are really PCIF1 m6Am. Linder 2015 Nat Methods 12:767 (miCLIP, the antibody-based single-base method) explicitly notes the cross-reactivity. Separately: while ~70% of mammalian METTL3-deposited m6A sites sit within the DRACH consensus (D=A/G/U, R=A/G, A=methylated, C=C, H=A/C/U), a non-trivial fraction are non-DRACH. Post-hoc filtering peaks by DRACH content drops real m6A peaks; DRACH should be reported as enrichment-relative-to-background (HOMER / MEME / ggseqlogo) on the PEAK SET as a whole, NOT as a per-peak filter. For unambiguous internal-m6A studies, restrict analysis to peaks past the first ~50 nt AND validate at high-stakes sites with an orthogonal method (miCLIP for single-base antibody validation; GLORI Liu 2023 Nat Biotechnol 41:355 for absolute stoichiometry; m6A-SAC-seq Hu 2022 Nat Biotechnol 40:1210; m6Anet for ONT direct-RNA confirmation).
Algorithmic Taxonomy
Tool / mode
Mechanism
Inputs
Output
Strength
Fails when
exomePeak2 (Liu 2022 NAR Genom Bioinform 4:lqac046)
Transcript-windowed Poisson GLM with on-the-fly GC-bias correction; supersedes exomePeak v1
paired IP/input BAM + TxDb / GTF
BED12 + RDS + per-peak fold-change / FDR
Transcript-aware; GC-aware; integrates motif annotation; modern field default
Slow on very large datasets; argument signatures shift between Bioconductor minor releases — verify against ?exomePeak2
MeTPeak (Cui 2016 Bioinformatics 32:i378)
HMM over sliding windows with Beta-binomial emission per window
paired IP/input BAM + GTF (or TxDb)
BED12
HMM smooths spatial dependency; better at low coverage
GitHub-only; unversioned; default window/step is 50/50 not the small values some tutorials suggest
Boost peak-calling sensitivity by leveraging DRACH motif as a prior
paired IP/input BAM + motif file
refined peak set
Improves sensitivity in low-coverage regions
Builds DRACH into the calling — DON'T use as evidence for DRACH enrichment downstream (circular)
m6ACali (recent ML peak filter; verify current citation against the project repo)
ML-based false-peak filter trained on exomePeak2 + MACS2 outputs across many cell lines
called peak set + IP/input BAM
refined peak set
Modern QC layer; cuts antibody artifact peaks
Trained on specific antibody clones; verify it generalises to the antibody used
Decision Tree by Scenario
Scenario
Recommended
Why wrong choices fail
Standard mammalian MeRIP, 3+ replicates per arm
exomePeak2 + DRACH confirmation; reconcile with MeTPeak as a second opinion
MACS3 misses GC-confounded peaks; MeTPeak alone gives less GC awareness
Viral / kilobase-broad peaks
MACS3 --broad --broad-cutoff 0.1 --keep-dup all
exomePeak2 splits broad enrichment into many small per-window peaks
Low-coverage / scarce-sample MeRIP
MeTPeak HMM smooths; exomePeak2 as cross-check
MACS3 default loses sensitivity at low coverage
Need single-nucleotide resolution
NOT MeRIP -- switch to miCLIP, m6Anet, GLORI, SAC-seq
MeRIP windows are ~100-200 nt; cannot resolve to base
5'UTR / cap-proximal peaks
Run normally BUT flag 5' peaks (within ~50 nt of TSS) as m6A-or-m6Am ambiguous; validate with PCIF1-KO if available
Antibody cross-reacts with m6Am; cannot assign without orthogonal data
Cross-tool reconciliation
Call with exomePeak2 + MeTPeak + MACS3 broad; intersect (NOT union) for high-confidence; report each separately
Union inflates false-positive rate; single-tool reports under-call ~30% of consensus peaks
Validation of high-stakes peak set
Cross-check against published m6A-Atlas / REPIC databases; orthogonal validation at top hits (miCLIP / GLORI / m6A-SAC-seq)
Single-method-single-study peaks have ~50% inter-study overlap (McIntyre 2020)
Wanting absolute stoichiometry
NOT MeRIP -- use GLORI (Liu 2023 Nat Biotechnol), SAC-seq (Hu 2022), eTAM-seq (Xiao 2023)
MeRIP IP fold-change is relative, not absolute
METTL3-KO validation experiment
Call peaks in WT and KO; peaks that DISAPPEAR in KO are m6A-dependent; peaks that REMAIN are antibody artifacts OR m6Am OR non-METTL3 modifications (METTL16, METTL5)
Calling only WT and assuming all peaks are m6A; many are not
Anti-m6A vs anti-m6Am specific analysis
For internal m6A only: exclude TSS-proximal peaks AND use GLORI / SAC-seq orthogonal validation; for m6Am specifically: m6Am-seq (Sun H 2021 Nat Commun 12:4778), m6ACE-seq, or PCIF1-KO subtraction
Antibody alone CANNOT distinguish — this is a chemistry problem, not a software problem
Methodology evolves; before any high-stakes peak-calling analysis, web-search "exomePeak2 Bioconductor release notes" and "MeRIP peak caller benchmark 2024" for current consensus parameters.
exomePeak2 Standard Workflow
Goal: Produce a transcript-aware set of m6A peaks with FDR and IP/input fold-change from paired IP/input genome BAM files, suitable as input to differential analysis, motif scanning, or downstream visualisation.
Approach: Build a TxDb from the matched GTF; pass paired IP/input BAM vectors with bam_ip and bam_input; let exomePeak2 handle GC-bias correction internally; export BED12 + RDS for downstream use; annotate against transcript features.
library(exomePeak2)
library(GenomicFeatures)
library(BSgenome.Hsapiens.UCSC.hg38)
txdb <- makeTxDbFromGFF('refs/annotation.gtf', format='gtf')
result <- exomePeak2(
bam_ip =c('aligned/IP_rep1.bam','aligned/IP_rep2.bam','aligned/IP_rep3.bam'),
bam_input =c('aligned/Input_rep1.bam','aligned/Input_rep2.bam','aligned/Input_rep3.bam'),
txdb = txdb,
genome = BSgenome.Hsapiens.UCSC.hg38,
paired_end =TRUE,
library_type ='unstranded',
save_dir ='exomepeak2_output',
experiment_name ='m6a_run1')# Inspect peaks: GRanges with metadata
peaks <- result
length(peaks)
head(as.data.frame(peaks))
exomePeak2() writes BED12 + RDS + per-peak fold-change / FDR to save_dir/experiment_name/. The txdb argument is the canonical interface; older tutorials use gff= (path) which is deprecated. BSgenome is required for GC correction; if unavailable, exomePeak2 falls back to a less-accurate GC-uncorrected mode.
MeTPeak HMM-Smoothed Alternative
Goal: Call peaks with HMM smoothing across spatial windows, useful when coverage is low or when peak boundaries are ambiguous from per-window negative-binomial tests alone.
Approach: MeTPeak accepts IP and INPUT BAM vectors plus either a GTF file path (GENE_ANNO_GTF=) or a TxDb object (TXDB=); defaults are WINDOW_WIDTH=50, SLIDING_STEP=50, FRAGMENT_LENGTH=100, MINIMAL_PEAK_LENGTH=FRAGMENT_LENGTH/2, MINIMAL_MAPQ=30. The example below uses GTF input with explicit defaults shown for transparency; adjust only with rationale.
MeTPeak accepts either GENE_ANNO_GTF= (a file path) or TXDB= (a TxDb object); the GTF path is the more common usage and is documented in the GitHub README. Output BED12 is at OUTPUT_DIR/EXPERIMENT_NAME/peak.bed. MeTPeak is GitHub-only (compgenomics/MeTPeak) and unversioned; pin a commit SHA in reproducible analyses.
MACS3 Broad-Peak Alternative
Goal: Call broad MeRIP peaks across the genome using the ChIP-seq sliding-window negative-binomial framework; useful for viral genomes where peaks span kilobases, or as a cross-caller second opinion.
Approach: MACS3 callpeak with --nomodel --extsize 150 --keep-dup all --broad. The --nomodel flag disables the ChIP-seq fragment-shift model (designed for DNA); --keep-dup all is REQUIRED because MACS3 default deduplicates and collapses MeRIP signal at high-coverage transcripts.
--keep-dup all is non-negotiable for MeRIP; the default --keep-dup 1 (keep one read per position) destroys real signal. --broad and --broad-cutoff 0.1 extend narrow peaks into broader regions, appropriate for MeRIP fragments. Output: narrowPeak + broadPeak + gappedPeak files in macs3_output/.
DRACH Motif Confirmation (Sanity Check, NOT a Filter)
Goal: Confirm that the called peak set is enriched for the DRACH consensus motif relative to genomic background, validating antibody specificity. NEVER post-hoc remove individual non-DRACH peaks.
Approach: Run HOMER findMotifsGenome.pl with -rna mode on peak centres ±50 bp against a length-matched random-shuffled background; expect DRACH-like consensus in the top motifs with E-value < 1e-50 for a well-behaved MeRIP dataset.
If DRACH enrichment is NOT observed in the peak set, the IP failed OR the wrong antibody was used OR the assay actually captured a different modification (m6A is centred in coding regions / 3'UTR; m1A is centred at TSS — different metagene signature). Do NOT proceed to differential analysis until DRACH is confirmed on the peak set as a whole.
Multi-Tool Consensus
Goal: Build a high-confidence peak set by intersecting multiple peak callers run on the same data; report both per-tool peak counts and the intersection.
Approach: Use bedtools intersect to combine exomePeak2, MeTPeak, and MACS3 broadPeak outputs; require at least 2-of-3 caller agreement for the high-confidence set.
Intersection (consensus) is the conservative choice; union inflates the false-positive rate (every caller's idiosyncratic false positives propagate). For published analyses, report both per-tool count AND consensus count; the ratio is a useful caller-agreement metric.
Per-Method Failure Modes
Anti-m6A antibody cross-reacts with m6Am at 5' peaks
Trigger: Peak called at the very 5' end of a transcript (within ~50 nt of TSS), attributed to METTL3-deposited internal m6A.
Mechanism: Anti-m6A antibodies cross-react with m6Am (the cap-adjacent N6,2'-O-dimethyladenosine at the +1 nucleotide of capped mRNAs), installed by PCIF1 / CAPAM (Akichika 2019 Science 363:eaav0080). METTL3 / METTL14 do NOT methylate the cap-adjacent position. Linder 2015 Nat Methods 12:767 explicitly noted the cross-reactivity; Mauer 2017 Nature 541:371 deepened the m6Am story.
Symptom: 5' peaks remain in METTL3-KO cells; agent infers METTL3-independent m6A writers when the peaks are really PCIF1 m6Am.
Fix: Flag peaks within ~50 nt of TSS as m6A-or-m6Am ambiguous. For unambiguous internal-m6A studies, exclude TSS-proximal peaks; for m6Am-specific studies, use PCIF1-KO subtraction or m6Am-seq (Sun H 2021); for orthogonal stoichiometric resolution, use GLORI / SAC-seq.
Peaks called at GC-extreme transcripts by MACS3 but not exomePeak2
Trigger: MACS3 broadPeak output has peaks at high-GC or low-GC transcripts that exomePeak2 does NOT call on the same BAMs.
Mechanism: exomePeak2 implements internal GC-bias correction; MACS3 does not. The IP step has GC bias because anti-m6A antibody pull-down efficiency varies with local GC content. MACS3 attributes GC-driven IP enrichment to true methylation; exomePeak2 corrects for it.
Fix: Trust exomePeak2 for transcript-aware analyses. Use MACS3 only as a second opinion or for broad / viral analyses. If a MACS3-only peak is biologically interesting, validate orthogonally.
DRACH filtering applied post-hoc
Trigger: Filtering called MeRIP peaks to retain only those containing a DRACH motif within the peak window.
Mechanism: ~70% of mammalian METTL3-deposited m6A sites sit within DRACH (Linder 2015), but a non-trivial fraction are non-DRACH. MeRIP peaks span ~100-200 nt; the methylated A is somewhere within the window but the peak boundary is not the modification position. Filtering by "no DRACH in window" rejects real peaks where DRACH sits at the edge or where the m6A is non-DRACH. The filter also creates circular validation — the filtered set is enriched for DRACH by construction.
Symptom: Peak count drops 30-50% after DRACH filtering; reviewers note the filter is not a standard convention.
Fix: Report DRACH enrichment as a SANITY CHECK on the peak set (HOMER E-value < 1e-50 expected) — never as a per-peak filter. For single-nucleotide methods (miCLIP, m6Anet, GLORI), the DRACH constraint is built into the calling model and need not be re-applied.
MACS3 default --keep-dup 1 on MeRIP
Trigger: MACS3 invoked without --keep-dup all; default behaviour is to retain one read per position.
Mechanism: MeRIP libraries have NO UMI (standard protocol); positional duplicates in MeRIP are a mix of PCR duplicates and biological re-sampling of high-coverage transcripts. Default --keep-dup 1 collapses the latter and destroys real signal at the most-abundant transcripts.
Symptom: MACS3 reports very few peaks at housekeeping genes (GAPDH, ACTB) despite obvious IP enrichment in IGV; peak count drops 5-20x compared to --keep-dup all.
Fix: Always pass --keep-dup all to MACS3 / MACS2 for MeRIP. This is the same logic as the do-NOT-dedup rule in merip-preprocessing.
MeTPeak called with wrong argument name for annotation
Trigger:metpeak(IP_BAM=..., INPUT_BAM=..., txdb=txdb_object) (lowercase txdb= rather than TXDB=).
Mechanism: MeTPeak's annotation arguments are GENE_ANNO_GTF= (GTF file path) or TXDB= (uppercase, TxDb object). Lowercase txdb= is not recognised. exomePeak2 uses lowercase txdb= instead, which leads to easy confusion between the two skills' APIs.
Fix: Pass either GENE_ANNO_GTF='annotation.gtf' (string path) or TXDB=txdb_object (capitalised). Verify argument casing against the installed MeTPeak source.
Single-tool peak set reported without cross-caller agreement
Trigger: Paper reports "18,234 m6A peaks" from exomePeak2 alone; downstream biology built on this single set.
Mechanism: Cross-tool concordance on MeRIP is empirically ~70% between exomePeak2 and MeTPeak on the same BAMs; single-tool reports include ~30% tool-specific calls. McIntyre 2020 Sci Rep 10:6590 documents this directly.
Fix: Run at least 2 callers (typically exomePeak2 + MeTPeak; or exomePeak2 + MACS3 broad); report the intersection as high-confidence; full per-tool counts as supplementary.
Transcriptome alignment passed to peak caller
Trigger: A transcriptome BAM (reads aligned to a transcripts.fa file) passed to exomePeak2 or MACS3 instead of a genome BAM.
Mechanism: Peak callers operate on genome BAMs and use the GTF to project peaks back to transcript features. Transcriptome BAMs have reads in per-transcript coordinates; the GTF cannot resolve these back to genome coordinates without re-alignment.
Fix: Align to GENOME with STAR / HISAT2 for downstream MeRIP peak calling (see merip-preprocessing). Transcriptome BAMs are for m6anet-analysis only.
Reconciliation: When Peak Callers Disagree
Pattern
Likely cause
Action
exomePeak2 calls a peak; MACS3 does not
GC-confounded; MACS3 calibration ignores GC
Trust exomePeak2 for transcript-aware analysis
MACS3 calls a broad peak; exomePeak2 calls 3-5 sub-peaks
Broad biology (e.g., long 3'UTR); exomePeak2 splits broad enrichment into per-window peaks
Merge exomePeak2 sub-peaks within 200 nt; report as broad
miCLIP single-nt site OUTSIDE MeRIP peak window
MeRIP window slightly shifted; OR low-coverage transcript
Inspect MeRIP coverage; consider miCLIP authoritative for single-nt identity
m6Anet high-confidence site at non-MeRIP-peak location
Non-DRACH site invisible to MeRIP antibody preferences; OR low MeRIP coverage; OR site is real but stoichiometry too low for MeRIP detection
Trust m6Anet for DRACH-context sites at adequate coverage
Two replicates concordant; third diverges
Failed IP in third replicate
Inspect IP enrichment QC in merip-preprocessing for the diverging replicate; consider exclusion
GLORI calls a high-stoichiometry site that MeRIP misses
MeRIP under-calls at low-expression transcripts; OR site outside common-core consensus
Trust GLORI for absolute stoichiometry; MeRIP is qualitative
exomePeak2 gives different peak counts across Bioconductor releases on same BAMs
Default-parameter or signature shifts between minor Bioconductor releases
Verify against ?exomePeak2; pin Bioconductor + exomePeak2 version in reproducible analyses
MACS3 narrowPeak vs broadPeak give very different counts
Tool-default thresholds differ; OR fragment length parameters differ
Harmonise thresholds across callers; reconcile via IDR-equivalent
exomePeak2 takes >24h on whole-genome BAMs
Large BAM + many transcripts
Subset to expressed transcripts; OR use more cores via downstream parallelisation
findMotifsGenome.pl error on chromosome naming
hg38 vs HG38 vs Hg38
Use lowercase hg38 consistently
ggseqlogo throws "sequences must be equal length"
Mixed-length sequences passed
Resize peak ranges to fixed width: resize(peaks, width=5, fix='center')
Anticipated Reviewer Pushback
Pushback
Response
"How many peak callers were used?"
Two minimum (exomePeak2 + MeTPeak or + MACS3); intersection reported as high-confidence; per-tool counts as supplementary
"Was filtering by DRACH applied?"
No — DRACH reported as enrichment-on-the-peak-set (HOMER E-value); per-peak DRACH filtering drops 5-10% real m6A sites
"How were 5'UTR peaks handled?"
Flagged peaks within 50 nt of TSS as m6A-or-m6Am ambiguous; restricted internal-m6A analyses to peaks past the 5'UTR; cited Linder 2015 / Mauer 2017 cross-reactivity
"What's the FDR threshold?"
exomePeak2 default FDR 0.05; MACS3 q-value 0.05; peaks reported with both fold-change and FDR
"Was orthogonal validation done?"
High-stakes sites validated against published miCLIP / GLORI / SAC-seq / m6A-Atlas; cross-method overlap reported
"Why exomePeak2 over MeTPeak?"
exomePeak2 implements GC-bias correction; MeTPeak does not. For low-coverage datasets MeTPeak HMM smoothing helps; for typical datasets exomePeak2 is the field default
"Were failed IPs checked for?"
Replicate IPs inspected via plotFingerprint AND per-transcript IP/input ratio distribution in merip-preprocessing BEFORE peak calling
"What's the cross-replicate peak overlap?"
Reported per pair; expect ~80% within-lab per McIntyre 2020
"Was the peak set intersected with m6A-Atlas?"
Yes — common-core overlap reported as a confidence anchor; novel peaks flagged for orthogonal validation
"Why weren't m6A-CLIP peaks called here?"
miCLIP / m6A-CLIP single-nucleotide methods live in clip-seq/peak-calling; this skill is for fragment-level MeRIP peak calling
References
Dominissini D, Moshitch-Moshkovitz S, Schwartz S et al (2012) Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 485(7397):201-206. doi:10.1038/nature11112
Meyer KD, Saletore Y, Zumbo P, Elemento O, Mason CE, Jaffrey SR (2012) Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons. Cell 149(7):1635-1646. doi:10.1016/j.cell.2012.05.003
Linder B, Grozhik AV, Olarerin-George AO, Meydan C, Mason CE, Jaffrey SR (2015) Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat Methods 12(8):767-772. doi:10.1038/nmeth.3453
Mauer J, Luo X, Blanjoie A et al (2017) Reversible methylation of m6Am in the 5' cap controls mRNA stability. Nature 541(7637):371-375. doi:10.1038/nature21022
Liu J, Yue Y, Han D et al (2014) A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat Chem Biol 10(2):93-95. doi:10.1038/nchembio.1432
Cui X, Meng J, Zhang S, Chen Y, Huang Y (2016) A novel algorithm for calling mRNA m6A peaks by modeling biological variances in MeRIP-seq data. Bioinformatics 32(12):i378-i385. doi:10.1093/bioinformatics/btw281
Meng J, Lu Z, Liu H, Zhang L, Zhang S, Chen Y, Rao MK, Huang Y (2014) A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package. Methods 69(3):274-281. doi:10.1016/j.ymeth.2014.06.008
Liu J, Zhang Z, Meng J et al (2022) exomePeak2: a peak calling and differential analysis tool for MeRIP-Seq with bias awareness. NAR Genom Bioinform 4(3):lqac046. doi:10.1093/nargab/lqac046
Zhang Y, Liu T, Meyer CA et al (2008) Model-based analysis of ChIP-Seq (MACS). Genome Biol 9(9):R137. doi:10.1186/gb-2008-9-9-r137
Akichika S, Hirano S, Shichino Y et al (2019) Cap-specific terminal N6-methylation of RNA by an RNA polymerase II-associated methyltransferase. Science 363(6423):eaav0080. doi:10.1126/science.aav0080
Boulias K, Toczydłowska-Socha D, Hawley BR et al (2019) Identification of the m6Am methyltransferase PCIF1 reveals the location and functions of m6Am in the transcriptome. Mol Cell 75(3):631-643.e8. doi:10.1016/j.molcel.2019.06.006
Liu C, Sun H, Yi Y et al (2023) Absolute quantification of single-base m6A methylation in the mammalian transcriptome using GLORI. Nat Biotechnol 41(3):355-366. doi:10.1038/s41587-022-01487-9
Hu L, Liu S, Peng Y et al (2022) m6A RNA modifications are measured at single-base resolution across the mammalian transcriptome. Nat Biotechnol 40(8):1210-1219. doi:10.1038/s41587-022-01243-z
Garcia-Campos MA, Edelheit S, Toth U et al (2019) Deciphering the m6A code via antibody-independent quantitative profiling. Cell 178(3):731-747.e16. doi:10.1016/j.cell.2019.06.013
McIntyre ABR, Gokhale NS, Cerchietti L, Jaffrey SR, Horner SM, Mason CE (2020) Limits in the detection of m6A changes using MeRIP/m6A-seq. Sci Rep 10(1):6590. doi:10.1038/s41598-020-63355-3
Heinz S, Benner C, Spann N et al (2010) Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell 38(4):576-589. doi:10.1016/j.molcel.2010.05.004
Related Skills
merip-preprocessing - IP/input BAM preparation, library complexity QC, and IP enrichment QC upstream of peak calling
m6a-differential - Compare peak sets between conditions; uses peaks called here as input
m6anet-analysis - Orthogonal validation of MeRIP peaks via ONT direct-RNA single-nucleotide resolution
modification-visualization - Metagene, browser-track, and peak-centred heatmap rendering of called peaks
