--- name: bio-atac-seq-atac-peak-calling description: Call accessible chromatin regions from ATAC-seq BAM files using MACS3, MACS2, Genrich, or HMMRATAC. Use when identifying open chromatin from aligned ATAC-seq, choosing between point-source vs HMM peak callers, applying ENCODE-style pseudoreplicate IDR, removing blacklist regions, or fixing 501bp consensus peaks for downstream differential analysis. tool_type: cli primary_tool: macs3 --- ## Version Compatibility Reference examples tested with: MACS3 3.0.2+, MACS2 2.2.9+, Genrich 0.6.1+, HMMRATAC 1.2+ (now bundled in MACS3 as `macs3 hmmratac`), samtools 1.19+, bedtools 2.31+, IDR 2.0.4+. Before using code patterns, verify installed versions match. If versions differ: - CLI: ` --version` then ` --help` to confirm flags If code throws unexpected errors, introspect the installed binary (` -h`) and adapt the example to match the actual CLI rather than retrying. # ATAC-seq Peak Calling **"Call accessible regions from my ATAC-seq BAM"** -> Identify Tn5-hypersensitive open chromatin, treating fragments as point insertion events (not protein-bound regions as in ChIP-seq) and accounting for the lack of input control. - CLI (canonical, ENCODE 4): `macs2 callpeak -t atac.bam -f BAM -g hs -n sample --nomodel --shift -75 --extsize 150 --keep-dup all -B --SPMR -p 0.01` (use `-f BAM`, not `-f BAMPE` -- BAMPE reads true fragment ends and ignores `--shift`/`--extsize`) - CLI (HMM-based, single sample): `macs3 hmmratac -i atac.bam -n sample --outdir hmm_out` - CLI (joint replicates): `Genrich -j -t rep1.bam,rep2.bam -o peaks.narrowPeak -e chrM -E blacklist.bed` The `-p 0.01` (loose) plus IDR is the ENCODE pattern: low stringency increases peak overlap between replicates, and IDR rescues the reproducible set. Single-sample workflows usually swap to `-q 0.05` instead. ## Algorithmic Taxonomy | Tool | Model | Treats fragments as | Min reps | Strength | Fails when | |------|-------|---------------------|----------|----------|------------| | MACS3/MACS2 | Local Poisson lambda + FDR | Point-source insertions (+/- shift) | 1 | Mature, ENCODE-default, fast, narrow + broad modes | Confounds NFR with broad accessible domains; no input means lambda from local genome only | | Genrich (ATAC mode -j) | q-value on log-transformed p-value, joint replicate model | Whole fragments (paired-end intervals) | 1 (multi-rep optional) | Treats reps jointly; can exclude chrM via `-e chrM`; auto blacklist via `-E`; PCR-dup removal via `-r` | Less peer-reviewed than MACS; thin literature; slow on deep libraries | | MACS3 hmmratac (was HMMRATAC) | 3-state HMM (open / nucleosomal / background) on fragment-size signal | Fragment-size classes | 1 | Models nucleosome periodicity directly; differentiates NFR and flanking nucleosomes | Needs >= 30M de-duplicated nuclear reads; memory-hungry; slow; flat fragment distribution -> garbage HMM | | HOMER `findPeaks -style dnase` | Fixed window + fold-change cutoff | Tag positions | 1 | Convenient for downstream HOMER motif analysis | Less calibrated p-values than MACS; window-size sensitive | | nf-core/atacseq | Wrapper (MACS2 by default) | Same as MACS2 | 1 | Reproducible Nextflow pipeline with QC built in | Only as good as the underlying caller | Methodology evolves; verify the current ENCODE ATAC-seq Standards (encodeproject.org pipelines/atac-seq) before locking parameters. ENCODE 4 still defaults to MACS2 (not MACS3) at time of writing; `macs3 callpeak` is API-compatible for ATAC parameters but not yet the official ENCODE binary. ## Shift-Extend vs BAMPE: The Critical Choice Two valid ways to feed paired-end ATAC into MACS: **Pattern A (ENCODE / "single-end-ified"):** `-f BAMPE` actually IGNORES `--shift/--extsize`. To activate them, use `-f BAM` and treat each end independently. ENCODE's pipeline uses `-f BAM --shift -75 --extsize 150` to model each Tn5 cut as a 150 bp window centered on the insertion site, ignoring fragment lengths. **Pattern B (paired-fragment):** `-f BAMPE` uses the full paired-end fragment span as the signal interval. Best when fragment lengths are biologically meaningful (e.g., NFR-only peak calling at 38/75 bp). In BAMPE mode, do NOT set `--shift/--extsize` (silently ignored, but confusing). For most bulk ATAC, Pattern A matches ENCODE convention and is reproducible against published peak sets. Pattern B can be more sensitive at narrow regulatory elements but does not match ENCODE outputs. ## Effective Genome Size `-g hs` and `-g mm` are MACS shorthands for old defaults. Modern values: | Genome | MACS shorthand | Actual mappable size | Source | |--------|---------------|----------------------|--------| | hg38 | `-g hs` (2.7e9) | 2.701e9 (50bp), 2.748e9 (75bp), 2.806e9 (100bp), 2.862e9 (150bp) | deepTools `effectiveGenomeSize` | | hg19 | `-g hs` (2.7e9) | 2.686e9 (50bp), 2.777e9 (100bp) | deepTools | | mm10 | `-g mm` (1.87e9) | 2.308e9 (50bp), 2.408e9 (75bp), 2.467e9 (100bp) | deepTools | | mm39 | none | 2.310e9 (50bp), 2.468e9 (100bp) | deepTools | Wrong size shifts every q-value but rarely changes peak ranks. Use `unique-kmers.py` (khmer) or the deepTools tabulated values for exact sizes; the shorthand is a decade-old approximation. ## Effective Genome Size: When It Matters **Trigger:** Comparing peaks across genome builds or species; reproducing published q-value cutoffs; hi-resolution lambda estimation. **Mechanism:** MACS estimates genome-wide lambda as `total_reads / effective_size`. Wrong size -> wrong null -> shifted q-values, especially at the marginal cutoff. **Symptom:** Peak counts diverge ~10-20% from published numbers when re-running an old dataset. **Fix:** Pull the read-length-matched value from deepTools `effectiveGenomeSize` table. For pipelines, parameterize this; never inline the shorthand for cross-study comparisons. ## Per-Tool Failure Modes ### MACS2/MACS3 -- Confounded NFR + broad accessibility **Trigger:** Cell type with extended open domains (e.g., active super-enhancers, MYOD1 regulons, locus-control regions). **Mechanism:** Default narrow-peak mode segments wide accessible domains into multiple smaller peaks at local lambda spikes; `--broad --broad-cutoff 0.1` merges them but inflates total length and breaks IDR comparability. **Symptom:** Peak count >> 200k for human bulk ATAC at ENCODE depth; mean peak width < 200 bp; visual inspection in IGV shows 3-5 calls under one continuous accessibility block. **Fix:** Run both narrow and broad; use narrow for differential analysis, broad for domain-level enrichment (e.g., super-enhancer overlap). Do NOT use `--call-summits` for broad mode. ### Genrich -- Replicate weighting and chrM exclusion **Trigger:** Replicates with very different library sizes; high-mitochondrial samples not pre-filtered. **Mechanism:** Genrich's joint mode combines the per-replicate p-values at each position via Fisher's method. Library-size imbalance dominates the joint p-value; chrM reads inflate background unless `-e chrM` is set. **Symptom:** Most-significant peaks cluster on chrM or on the largest-library replicate's high-coverage regions. **Fix:** Always pass `-e chrM` (Genrich 0.6+) and `-E blacklist.bed`. Down-sample BAMs to common depth (`samtools view -s`) before joint calling if libraries differ >2x. Add `-r` to remove PCR duplicates inside Genrich, OR pre-deduplicate (do not do both). ### MACS3 hmmratac (HMMRATAC) -- Depth and fragment-size dependence **Trigger:** Library < 25M nuclear reads, or libraries with degraded chromatin and flat fragment-size distribution. **Mechanism:** The 3-state HMM is trained from fragment-size classes (NFR ~50 bp, mono ~200 bp, di ~400 bp peaks). Without periodicity the emission distributions collapse and the HMM cannot separate states. **Symptom:** Output BED is empty, or all peaks are tiny (~150 bp) with no nucleosome flanks called; runtime explodes (>24h) on shallow data. **Fix:** Verify fragment-size periodicity in QC first (atac-qc skill). If flat, fall back to MACS3 callpeak. HMMRATAC needs deep coverage (a practical minimum around 30M deduplicated nuclear reads). ### HOMER findPeaks -- Window-size sensitivity **Trigger:** Default `-style dnase` uses 75 bp peaks; ATAC peaks are 250-500 bp typically. **Mechanism:** HOMER's window-based caller does not auto-fit width to ATAC. **Fix:** Use `-style factor -size 150` for narrow ATAC peaks, or skip HOMER for peak calling and use it only for downstream motif analysis on MACS peaks. ### Aligner choice -- chromap vs bwa-mem2 vs bowtie2 affects peak shape **Trigger:** Switching aligners between datasets and expecting reproducible peaks. **Mechanism:** chromap (Zhang 2021) applies its own ATAC-specific 4 bp / -5 bp Tn5 shift before fragment output; bwa-mem2 and bowtie2 do not. Downstream `--shift -75 --extsize 150` parameters are calibrated for unshifted bwa/bowtie BAMs; applying them to chromap output double-shifts the signal. **Symptom:** Peaks called from chromap output are shifted by ~5-10 bp relative to bwa output at the same locus. **Fix:** When using chromap, drop `--shift` and `--extsize` (chromap's pre-shift is sufficient) OR omit chromap's `--Tn5-shift` (the shift is opt-in, applied only when that flag or an ATAC preset is set) so it is not double-applied, then proceed with standard MACS parameters. Document the aligner version and any shift choices in methods. Within a project, pin the aligner. ### Single-sample (no replicate) -- Rotation / circular-shift permutation **Trigger:** Single biological sample without any replicate for IDR. **Mechanism:** IDR requires two replicates by construction. For n=1, statistical confidence per peak comes from local background (Poisson p-value) but reproducibility cannot be assessed. **Fix:** Apply a stricter `-q 0.01` (vs ENCODE `-p 0.01` + IDR pattern) and additionally apply rotation/circular-shift permutation: shift the BAM cuts by a random distance modulo each chromosome and re-call peaks; the per-peak persistence rate across rotations is a non-parametric reproducibility proxy. Document this is a single-sample heuristic, not ENCODE-compliant. ## ENCODE 3 vs ENCODE 4 Differences | Feature | ENCODE 3 (legacy) | ENCODE 4 (current) | |---------|-------------------|---------------------| | Per-rep significance threshold | `-q 0.05` directly | `-p 0.01` (loose) + IDR | | Pseudoreplicate IDR cutoff | Not formalized | `--idr-threshold 0.10` self-consistency | | TSS enrichment threshold | >= 6 (older) | >= 7 (hg38, GENCODE v29) | | Mt fraction expectation | < 25% | < 20% (Omni-ATAC < 5%) | | Blacklist | v1 | v2 (Amemiya 2019) | | Default genome size | hardcoded `hs`/`mm` | encouraged: deepTools effectiveGenomeSize | To reproduce a published ENCODE 3 dataset, pin the original pipeline and threshold exactly. ENCODE 4 results are not directly numerically comparable to ENCODE 3 even on the same input BAM. ## Super-Enhancer Detection For active super-enhancer (SE) annotation alongside narrow-peak workflow, ROSE (Whyte 2013) and LILY (Boeva 2017) stitch ATAC or H3K27ac peaks separated by < 12.5 kb and rank by signal: ```bash # ROSE expects H3K27ac BAM but works on ATAC narrowPeak with care ROSE_main.py -g hg38 -i atac_peaks.gff -r atac.bam -o rose_out/ -t 2500 ``` ROSE-style stitching is complementary to MACS3 narrow peaks: narrow peaks for differential analysis; SE annotation for biology interpretation. SE calls require H3K27ac input for definitive annotation; ATAC alone produces "stretch enhancers" that overlap but are not identical to H3K27ac SE. ## ENCODE 4 ATAC-seq Pipeline (Reference Implementation) The exact ENCODE pattern produces the most-comparable peak sets: ```bash # Per-replicate peak calling (loose threshold) macs2 callpeak \ -t rep1.filt.dedup.bam \ -f BAM -g hs \ -n rep1 --outdir peaks/rep1/ \ --nomodel --shift -75 --extsize 150 \ --keep-dup all \ -B --SPMR \ -p 0.01 # Pooled (all replicates) macs2 callpeak \ -t rep1.filt.dedup.bam rep2.filt.dedup.bam \ -f BAM -g hs -n pooled --outdir peaks/pooled/ \ --nomodel --shift -75 --extsize 150 --keep-dup all -B --SPMR -p 0.01 # Pseudoreplicates (two independent 50% subsamples; approximate, not a disjoint partition) samtools view -b -h -s 1.5 rep1.filt.dedup.bam > rep1.psr1.bam # seed.fraction samtools view -b -h -s 2.5 rep1.filt.dedup.bam > rep1.psr2.bam # different seed # (call peaks on each pseudoreplicate the same way) ``` `--SPMR` writes signal as Signal Per Million Reads (normalized bedGraph). `-p 0.01` is intentionally loose; IDR will tighten to a reproducible set. ## IDR for Reproducible Peaks **Goal:** Find peaks reproducible across biological replicates at controlled IDR. **Approach:** Score paired peak lists by signalValue, fit IDR's two-component mixture (reproducible + noise), threshold at IDR <= 0.05 (true reps) or 0.10 (pseudoreplicates). ```bash # Sort peaks by p-value (column 8) so IDR scores by significance sort -k8,8nr rep1_peaks.narrowPeak > rep1.sorted.narrowPeak sort -k8,8nr rep2_peaks.narrowPeak > rep2.sorted.narrowPeak # True replicates -- threshold IDR <= 0.05 idr --samples rep1.sorted.narrowPeak rep2.sorted.narrowPeak \ --input-file-type narrowPeak --rank p.value \ --output-file true_reps.idr \ --idr-threshold 0.05 --plot --log-output-file idr.log # Pseudoreplicates -- threshold IDR <= 0.10 (looser, ENCODE Nself <= 2 rule) idr --samples psr1_peaks.narrowPeak psr2_peaks.narrowPeak \ --input-file-type narrowPeak --rank p.value \ --output-file psr.idr --idr-threshold 0.10 --plot ``` **ENCODE consistency rules:** Nt = peaks passing IDR on true reps; Nself = peaks passing IDR on pseudoreps. Library passes if `max(Nt, Nself) / min(Nt, Nself) <= 2`. If both ratios > 2, the library is rejected. **IDR fails when:** Ranking column choice matters. `--rank p.value` (column 8) is robust; `--rank signal.value` (column 7) breaks if MACS pile-up scaling differs between replicates. ## Decision Tree by Experimental Scenario | Scenario | Recommended caller | Why | |----------|-------------------|-----| | Bulk ATAC, 2-3 reps, depth >= 25M | MACS2 ENCODE pipeline + IDR | Reproducible, comparable to published peaksets | | Bulk ATAC, 1 sample (no rep) | MACS3 callpeak with `-q 0.05`; do not run IDR | IDR is meaningless without reps; tighter q-value substitutes | | Bulk ATAC, depth >= 30M, want NFR + flanking nuc structure | MACS3 hmmratac | HMM separates NFR from nucleosome flanks | | Multi-replicate joint analysis where rep weighting is symmetric | Genrich `-j` ATAC mode | Joint p-value across reps; built-in chrM and blacklist | | Cell type with broad super-enhancer accessibility | MACS3 `--broad --broad-cutoff 0.1` for SE; narrow for differential | Domain-level inference vs site-level | | FFPE / degraded chromatin (flat fragment dist) | MACS3 callpeak with stringent `-q 0.01`; never HMMRATAC | HMM needs fragment periodicity | | scATAC pseudobulk per cluster | MACS3 callpeak per cluster + iterative overlap | See atac-seq/single-cell-atac | | Want fixed-width consensus peaks for differential | Call broadly, then re-center to summits +/- 250 bp | See atac-seq/consensus-peakset | | Plant / non-model organism | MACS3 with `-g `; verify size empirically | Default `-g hs/mm` invalid; compute via khmer | ## Reconciliation: When Callers Disagree | Pattern | Likely cause | Action | |---------|--------------|--------| | MACS narrow peaks much fewer than Genrich | Genrich q-cutoff different default (`-q 0.05` log-scale, MACS `-q 0.05` linear) | Re-run with `-q 0.01` (Genrich) for parity | | HMMRATAC misses peaks MACS finds | Library too shallow OR fragment-size periodicity weak | Trust MACS; HMMRATAC is depth-sensitive | | HMMRATAC calls peaks MACS misses | HMM is sensitive to mid-strength accessibility flanked by phased nucleosomes | Inspect; often genuine but unconfirmed by short-fragment signal | | Same peak called by all but width 2x different | Broad mode vs narrow mode mismatch | Standardize: re-center to summit +/- 250 bp for differential | | Per-rep MACS calls peak; pooled MACS does not | One rep dominates; lambda smoothes it out in pooled | Trust pooled + IDR over per-rep counts | **Operational rule for high-confidence reporting:** Require a peak to pass IDR <= 0.05 on true replicates AND survive blacklist/greylist filtering AND have mean signalValue >= 5 across reps. Two callers from different families (MACS + Genrich) agreeing within 250 bp is acceptable evidence when IDR is unavailable. ## Blacklist and Greylist ```bash # ENCODE blacklist (Amemiya 2019) -- always remove wget https://github.com/Boyle-Lab/Blacklist/raw/master/lists/hg38-blacklist.v2.bed.gz gunzip hg38-blacklist.v2.bed.gz bedtools intersect -v -a peaks.narrowPeak -b hg38-blacklist.v2.bed > peaks.no_blacklist.narrowPeak # Sample-specific greylist (input-derived high-signal regions; rarely available for ATAC) # For ATAC, ENCODE recommends pooling all samples' top-percentile signal and removing # regions exceeding 100x median coverage as a "soft greylist" ``` Blacklist is mandatory; greylist is optional and most useful when the same library prep produces consistent artifact regions across samples. ## NFR-Only Peak Calling **Goal:** Call peaks using only sub-nucleosomal fragments (<100 bp) for sharper TF-binding-relevant accessibility. **Approach:** Pre-filter BAM to short fragments, then call peaks with parameters scaled to the smaller fragment length. ```bash samtools view -h sample.dedup.bam | \ awk 'substr($0,1,1)=="@" || ($9 > 0 && $9 < 100) || ($9 < 0 && $9 > -100)' | \ samtools view -b > nfr.bam samtools index nfr.bam macs2 callpeak -t nfr.bam -f BAM -g hs -n sample_nfr \ --nomodel --shift -37 --extsize 75 \ --keep-dup all -p 0.01 ``` `--shift -37 --extsize 75` halves both parameters to match shorter fragments; this is a fragment-scaled convention for NFR-focused input, not a TOBIAS-specified setting (TOBIAS instead applies the +4/-5 Tn5 correction to the full BAM via ATACorrect). ## Output Files (narrowPeak) | Column | Field | Notes | |--------|-------|-------| | 1-3 | chrom, start, end | 0-based, half-open | | 4 | name | MACS auto-numbers | | 5 | score | Min(int(-10*log10(qvalue)), 1000) | | 6 | strand | `.` for ATAC | | 7 | signalValue | Fold enrichment over local lambda | | 8 | pValue | -log10 p | | 9 | qValue | -log10 q (BH-FDR) | | 10 | summit_offset | Peak summit relative to start | Convert to bigWig for browsers: `sort -k1,1 -k2,2n sample_treat_pileup.bdg > sample.sorted.bdg && bedGraphToBigWig sample.sorted.bdg chrom.sizes sample.bw` (bedGraphToBigWig is multi-pass and cannot read from a pipe/stdin, so sort to a file first). ## Common Errors | Error / symptom | Cause | Solution | |-----------------|-------|----------| | `--shift/--extsize ignored` warning | Used `-f BAMPE` with these flags | Switch to `-f BAM` or remove the flags | | 0 peaks called | Forgot `--nomodel`; MACS tries to build a shifting model and fails | Add `--nomodel --shift -75 --extsize 150` | | Peak count >> 500k | Did not deduplicate; or did not remove chrM; or `-q` too loose | Pre-filter (samtools view -F 1804 -q 30; samtools idxstats); use `-q 0.01` | | `Sequence chrM not found` (Genrich) | Wrong chromosome name in `-e` flag (chrM vs MT) | Match BAM header naming convention | | HMMRATAC out of memory | Deep library / large genome; the current tool is `macs3 hmmratac` (Python, not Java) | Increase available RAM and use a scratch `--outdir`; the `-Xmx`/`HMMRATAC.jar` heap flags apply only to the deprecated standalone Java HMMRATAC | | Peaks shifted by 75 bp from expected positions | Forgot `--shift -75` (cuts at one end of read) | Add the shift; positions are now centered on Tn5 cut site | | IDR returns 0 reproducible peaks | Sorted by wrong column; ranks are random | Sort each peakset by `-k8,8nr` (p-value descending) | ## References - Buenrostro JD et al 2013 Nat Methods 10:1213 (ATAC-seq protocol) - Corces MR et al 2017 Nat Methods 14:959 (Omni-ATAC protocol) - Corces MR et al 2018 Science 362:eaav1898 (iterative-overlap fixed-width 501 bp consensus peaks) - Tarbell ED & Liu T 2019 Nucleic Acids Res 47:e91 (HMMRATAC) - Gaspar JM, Genrich: detecting sites of genomic enrichment (github.com/jsh58/Genrich; no published paper) - Li Q et al 2011 Ann Appl Stat 5:1752 (IDR framework) - Landt SG et al 2012 Genome Res 22:1813 (ENCODE/modENCODE peak calling guidelines, IDR Nself rule) - Amemiya HM et al 2019 Sci Rep 9:9354 (ENCODE blacklist v2) - ENCODE ATAC-seq Standards (encodeproject.org/atac-seq) -- canonical pipeline parameters ## Related Skills - atac-seq/atac-qc - Verify TSS enrichment, FRiP, and fragment periodicity before calling - atac-seq/consensus-peakset - Combine per-sample peaks into a fixed-width differential-ready set - atac-seq/single-cell-atac - Pseudobulk peak calling per cluster - atac-seq/differential-accessibility - Downstream DiffBind/csaw/DESeq2 testing - atac-seq/deep-learning-atac - chromBPNet bias-corrected per-base profiles as alternative input - read-alignment/bowtie2-alignment - Upstream ATAC alignment - alignment-files/duplicate-handling - Pre-call dedup with Picard MarkDuplicates - chip-seq/peak-calling - ChIP-seq comparison (uses input control) - chip-seq/super-enhancers - ROSE / LILY for super-enhancer annotation - genome-intervals/bed-file-basics - Peak file manipulation