Orchestrates an end-to-end MeRIP-seq / m6A-seq analysis from raw FASTQ to differential m6A peak calls and metagene plots, chaining fastp adapter trimming, STAR splice-aware alignment (NO deduplication for non-UMI MeRIP), deepTools replicate-concordance + IP-enrichment QC, PreSeq saturation curves, exomePeak2 (transcript-aware Poisson GLM) peak calling, optional MACS3 broad-peak cross-check, DRACH motif confirmation as a sanity check (NOT a per-peak filter), exomePeak2 differential calling via the four-BAM-vector interface (bam_ip + bam_input control; bam_treated_ip + bam_treated_input treatment), ChIPseeker annotation, and the canonical Guitar metagene with stop-codon enrichment as the biological QC anchor. Use when running a complete MeRIP analysis from raw reads, when chaining the constituent epitranscriptomics skills (merip-preprocessing -> m6a-peak-calling -> m6a-differential -> modification-visualization), or when wrapping the pipeline in Snakemake / Nextflow.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Reference examples tested with: STAR 2.7.11+, samtools 1.19+, fastp 0.23+, deepTools 3.5+, PreSeq 3.2+, exomePeak2 1.14+ (Bioconductor 3.18+), MACS3 3.0+, ChIPseeker 1.38+, Guitar 2.18+, BSgenome.Hsapiens.UCSC.hg38 1.4+, TxDb.Hsapiens.UCSC.hg38.knownGene 3.18+, HOMER 4.11+.
Before using code patterns, verify installed versions match. If versions differ:
packageVersion('<pkg>') then ?function_name to verify parameters<tool> --version then <tool> --help to confirm flagsIf code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
exomePeak2 has NO mode= or experiment_design= argument; differential is triggered by populating bam_treated_ip + bam_treated_input. MeTPeak defaults are WINDOW_WIDTH=50, SLIDING_STEP=50, FRAGMENT_LENGTH=100. MACS3 default --keep-dup is 1 and MUST be overridden to all for non-UMI MeRIP. Guitar txTxdb= is the modern argument name (older releases used txdb=).
"Analyze my MeRIP-seq data from FASTQ to differential m6A peaks" -> Orchestrate read alignment (STAR splice-aware to GENOME), IP-enrichment QC (deepTools plotFingerprint, replicate Spearman, PreSeq saturation), m6A peak calling (exomePeak2 transcript-aware default, MACS3 broad as cross-check), DRACH motif sanity check (HOMER), exomePeak2 differential via the four-BAM-vector interface, ChIPseeker feature annotation, and Guitar transcript-feature metagene confirming canonical stop-codon enrichment. Defer per-skill deep treatment to epitranscriptomics/merip-preprocessing, epitranscriptomics/m6a-peak-calling, epitranscriptomics/m6a-differential, and epitranscriptomics/modification-visualization.
FASTQ -> fastp trim -> STAR genome align -> samtools sort/index -> deepTools QC + PreSeq saturation
-> exomePeak2 peak calling (+ MeTPeak / MACS3 cross-check)
-> HOMER DRACH sanity check
-> exomePeak2 differential (bam_ip + bam_treated_ip)
-> ChIPseeker feature annotation
-> Guitar metagene (stop-codon QC anchor) + pyGenomeTracks browser figures
fastp \
--in1 raw/IP_R1.fastq.gz --in2 raw/IP_R2.fastq.gz \
--out1 trimmed/IP_R1.fq.gz --out2 trimmed/IP_R2.fq.gz \
--json qc/IP_fastp.json --html qc/IP_fastp.html \
--length_required 25 --detect_adapter_for_pe --thread 8
fastp \
--in1 raw/Input_R1.fastq.gz --in2 raw/Input_R2.fastq.gz \
--out1 trimmed/Input_R1.fq.gz --out2 trimmed/Input_R2.fq.gz \
--json qc/Input_fastp.json --html qc/Input_fastp.html \
--length_required 25 --detect_adapter_for_pe --thread 8
Standard non-UMI MeRIP: do NOT pass --umi. See epitranscriptomics/merip-preprocessing for the do-NOT-dedup rationale.
STAR --runMode alignReads \
--genomeDir refs/star_index \
--readFilesIn trimmed/IP_R1.fq.gz trimmed/IP_R2.fq.gz \
--readFilesCommand zcat \
--outSAMtype BAM SortedByCoordinate \
--outFilterMultimapNmax 20 \
--outSAMattributes NH HI AS nM NM MD \
--outFileNamePrefix aligned/IP_ \
--runThreadN 12
samtools index aligned/IP_Aligned.sortedByCoord.out.bam
Repeat for Input. Align to GENOME (not transcriptome) for downstream MeRIP peak calling. Do NOT deduplicate (no UMI in standard MeRIP).
multiBamSummary bins \
--bamfiles aligned/IP_rep*.bam aligned/Input_rep*.bam \
--binSize 10000 --numberOfProcessors 8 \
-o qc/cov.npz
plotCorrelation --corData qc/cov.npz --corMethod spearman --skipZeros \
--whatToPlot heatmap --colorMap RdYlBu_r --plotNumbers \
-o qc/replicate_correlation.pdf
plotFingerprint \
--bamfiles aligned/IP_rep*.bam aligned/Input_rep*.bam \
--skipZeros --numberOfProcessors 8 \
--outQualityMetrics qc/fingerprint_metrics.tab \
-o qc/fingerprint.pdf
preseq lc_extrap -B -o qc/IP_rep1_lc_extrap.txt aligned/IP_rep1_Aligned.sortedByCoord.out.bam
For peak-count comparison across conditions, rarefy BAMs to a common unique-read depth informed by the saturation curve before calling peaks.
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 to exomePeak2() with txdb and genome (BSgenome) for GC correction; export BED12 + RDS to save_dir/experiment_name/.
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'
)
peaks <- result
length(peaks)
exomePeak2() writes BED12 + RDS + per-peak fold-change / FDR to save_dir/experiment_name/.
macs3 callpeak \
--treatment aligned/IP_rep*.bam \
--control aligned/Input_rep*.bam \
--format BAMPE --gsize hs \
--nomodel --extsize 150 \
--keep-dup all \
--broad --broad-cutoff 0.1 --qvalue 0.05 \
--outdir macs3_output --name m6a_run1
--keep-dup all is non-negotiable for non-UMI MeRIP (default --keep-dup 1 destroys signal at high-coverage transcripts).
findMotifsGenome.pl \
exomepeak2_output/m6a_run1/peaks.bed \
hg38 motif_output \
-rna -size 100 -len 5,6 -p 8
Report DRACH enrichment on the peak set as a sanity check (E-value < 1e-50 expected). NEVER post-hoc filter individual peaks by DRACH.
Goal: Identify m6A peaks that change between control and treatment conditions, with per-peak log2FC + FDR, using exomePeak2's integrated peak-calling + differential interface.
Approach: Populate bam_ip + bam_input with the control arm and bam_treated_ip + bam_treated_input with the treatment arm; populating the treated arms triggers differential mode (there is NO mode= argument). Apply effect-size + FDR filters downstream.
library(exomePeak2)
library(GenomicFeatures)
library(BSgenome.Hsapiens.UCSC.hg38)
txdb <- makeTxDbFromGFF('refs/annotation.gtf', format='gtf')
ctrl_ip <- c('aligned/ctrl_IP1.bam', 'aligned/ctrl_IP2.bam', 'aligned/ctrl_IP3.bam')
ctrl_input <- c('aligned/ctrl_Input1.bam', 'aligned/ctrl_Input2.bam', 'aligned/ctrl_Input3.bam')
treat_ip <- c('aligned/treat_IP1.bam', 'aligned/treat_IP2.bam', 'aligned/treat_IP3.bam')
treat_input <- c('aligned/treat_Input1.bam', 'aligned/treat_Input2.bam', 'aligned/treat_Input3.bam')
diff_result <- exomePeak2(
bam_ip = ctrl_ip,
bam_input = ctrl_input,
bam_treated_ip = treat_ip,
bam_treated_input = treat_input,
txdb = txdb,
genome = BSgenome.Hsapiens.UCSC.hg38,
paired_end = TRUE,
library_type = 'unstranded',
peak_calling_mode = 'exon',
save_dir = 'exomepeak2_diff_output',
experiment_name = 'ctrl_vs_treat'
)
diff_table <- as.data.frame(diff_result)
sig <- diff_table[diff_table$padj < 0.05 & abs(diff_table$log2FC) > 0.5, ]
nrow(sig)
exomePeak2 has NO mode= or experiment_design= argument. Populating bam_treated_ip + bam_treated_input triggers differential output. For batch / antibody-lot covariate adjustment, fall through to featureCounts-on-peaks -> DESeq2 (see epitranscriptomics/m6a-differential).
library(ChIPseeker)
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
library(rtracklayer)
peaks <- import('exomepeak2_output/m6a_run1/peaks.bed')
anno <- annotatePeak(peaks, TxDb=TxDb.Hsapiens.UCSC.hg38.knownGene, level='transcript')
plotAnnoBar(anno)
plotDistToTSS(anno)
Flag peaks within ~50 nt of TSS as m6A-or-m6Am ambiguous (antibody cross-reactivity with PCIF1-deposited cap m6Am).
library(Guitar)
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
GuitarPlot(
txTxdb = TxDb.Hsapiens.UCSC.hg38.knownGene,
stBedFiles = list('exomepeak2_output/m6a_run1/peaks.bed'),
saveToPDFprefix = 'figures/m6a_metagene'
)
Expected pattern: peak density rises toward and peaks near the stop codon (3'UTR-proximal end of CDS). If absent, suspect IP failure or wrong antibody; do NOT proceed to downstream interpretation.
#!/usr/bin/env bash
set -euo pipefail
STAR_INDEX=$1
GTF=$2
IP_R1=$3
IP_R2=$4
INPUT_R1=$5
INPUT_R2=$6
OUTPUT_DIR=$7
mkdir -p "${OUTPUT_DIR}"/{qc,trimmed,aligned,peaks,figures}
fastp --in1 "${IP_R1}" --in2 "${IP_R2}" \
--out1 "${OUTPUT_DIR}/trimmed/IP_R1.fq.gz" --out2 "${OUTPUT_DIR}/trimmed/IP_R2.fq.gz" \
--json "${OUTPUT_DIR}/qc/IP_fastp.json" --length_required 25 --detect_adapter_for_pe --thread 8
fastp --in1 "${INPUT_R1}" --in2 "${INPUT_R2}" \
--out1 "${OUTPUT_DIR}/trimmed/Input_R1.fq.gz" --out2 "${OUTPUT_DIR}/trimmed/Input_R2.fq.gz" \
--json "${OUTPUT_DIR}/qc/Input_fastp.json" --length_required 25 --detect_adapter_for_pe --thread 8
for sample in IP Input; do
STAR --runMode alignReads --genomeDir "${STAR_INDEX}" \
--readFilesIn "${OUTPUT_DIR}/trimmed/${sample}_R1.fq.gz" "${OUTPUT_DIR}/trimmed/${sample}_R2.fq.gz" \
--readFilesCommand zcat --outSAMtype BAM SortedByCoordinate \
--outFilterMultimapNmax 20 \
--outFileNamePrefix "${OUTPUT_DIR}/aligned/${sample}_" --runThreadN 12
samtools index "${OUTPUT_DIR}/aligned/${sample}_Aligned.sortedByCoord.out.bam"
done
macs3 callpeak \
--treatment "${OUTPUT_DIR}/aligned/IP_Aligned.sortedByCoord.out.bam" \
--control "${OUTPUT_DIR}/aligned/Input_Aligned.sortedByCoord.out.bam" \
--format BAMPE --gsize hs --nomodel --extsize 150 --keep-dup all \
--broad --broad-cutoff 0.1 --qvalue 0.05 \
--outdir "${OUTPUT_DIR}/peaks" --name m6a
The full pipeline (incl. exomePeak2 peak calling, DRACH check, ChIPseeker annotation, Guitar metagene) is best orchestrated in Snakemake or Nextflow with the per-skill recipes from the four epitranscriptomics/ skills.
| Checkpoint | Expected | Action if Failed |
|---|---|---|
| Properly-paired rate (samtools flagstat) | >=85% | Check trimming and adapter contamination |
| Replicate Spearman within condition (10 kb bins) | >=0.85 IP-IP | Inspect divergent replicate; consider exclusion |
| plotFingerprint IP-vs-input JS distance | >=0.5 | Suspect failed IP if lower |
| Saturation plateau depth | ~30-60M unique reads | Sequence deeper if not plateaued |
| DRACH motif enrichment (HOMER, peak set) | E-value < 1e-50 | Suspect IP failure or wrong antibody |
| Stop-codon enrichment in Guitar metagene | Clear 3'UTR-proximal peak | Suspect IP failure, wrong antibody, or non-m6A modification |
| 5'UTR peaks fraction | Note ambiguity zone (~50 nt of TSS) | Flag as m6A-or-m6Am ambiguous; PCIF1 cross-reactivity |
| File | Description |
|---|---|
exomepeak2_output/m6a_run1/peaks.bed | exomePeak2 peak BED12 |
exomepeak2_diff_output/ctrl_vs_treat/... | Differential peaks with log2FC + FDR |
motif_output/ | HOMER DRACH motif enrichment report |
figures/m6a_metagene.pdf | Guitar transcript-feature metagene (stop-codon QC anchor) |
qc/replicate_correlation.pdf | deepTools Spearman heatmap |
qc/fingerprint.pdf | deepTools Lorenz IP-enrichment plot |
qc/IP_rep*_lc_extrap.txt | PreSeq saturation curves |
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