FridrichMethod Version Compatibility
Reference examples tested with: deepTools 3.5+, phantompeakqualtools 1.2.2+, ChIPQC 1.42+, IDR 2.0.4+, samtools 1.19+, bedtools 2.31+, pysam 0.22+, pybedtools 0.9+, MACS2 2.2.9+, MACS3 3.0.4+.
Verify versions before relying on numerical thresholds — phantompeakqualtools has known R-version compatibility issues with R ≥ 4.0 (use kundajelab fork or pin to R 3.6).
ChIP-seq Quality Control
"Should I trust this ChIP-seq experiment?" -> Validate antibody, fragmentation, enrichment, replicate concordance, library complexity, and absence of hyper-ChIPable artifacts before committing to downstream peak calling and differential analysis.
- CLI:
Rscript run_spp.R -c=chip.bam -out=cc.txt(NSC/RSC),plotFingerprint -b chip.bam input.bam(enrichment shape),idr --samples rep1.np rep2.np(replicate IDR) - R: ChIPQC package (Carroll & Stark; computes the full ENCODE metric battery)
- Python: pysam + pybedtools for custom FRiP and library-complexity metrics
ChIP-seq fails for many independent reasons. The QC metrics below probe distinct failure modes — passing one metric does not rescue another. Antibody failure cannot be fixed by sequencing more.
The Antibody Problem is the Real Problem
Every downstream metric is conditional on antibody specificity. "ChIP-grade" on a vendor datasheet is marketing, not validation. Run the cascade:
| Step | What | Why |
|---|---|---|
| 1. Western blot | Expected MW + KO/KD negative | Confirms the antibody hits a band of the right size and loses signal in KO |
| 2. IP-Western | Pulls down the protein | Confirms IP recovery, not just recognition |
| 3. ChIP-qPCR | Known positive + known negative loci | First chromatin-context test; cheap |
| 4. ChIP-seq biological replicate | Two independent biological replicates | Reproducibility check |
| 5. KO/KD orthogonal | ChIP in KO/KD cells | Gold-standard: signal should drop to background |
| 6. Peptide array (histones) | Epicypher SNAP-ChIP or equivalent | Tests modification-state specificity |
Histone modification cross-reactivity is universal: H3K9me2 vs H3K9me3, H3K27me2 vs H3K27me3, and H3K4me1 vs H3K4me2 antibodies routinely show 10-30% cross-reactivity. Polyclonals vary lot-to-lot. CRISPR-knockout-validated lots from CST and Epicypher are the modern standard. Always record antibody catalog number + lot in methods.
Fragment-Size Distribution is a Free Diagnostic
The fragment-size distribution from a properly prepared ChIP BAM is itself a quality readout:
| Distribution shape | Interpretation |
|---|---|
| Sharp peak at ~50-100 bp (sub-nucleosomal) | Direct TF binding; expected for well-fragmented TF ChIP |
| Sharp peak at ~150 bp + secondary at ~300 bp | Mono- + di-nucleosomal; expected for histone ChIP |
| Bimodal at 150 + 300, no sub-nucleosomal | Histone-only signal; in TF ChIP, suggests trapping / hyper-ChIPable |
| Broad continuum 100-1000 bp | Over-sonication; biology lost; cannot be rescued |
| No peak structure, flat | Severe over-sonication or library prep failure |
# Quick diagnostic — count fragment sizes from properly-paired reads
samtools view -f 0x2 sample.bam | awk '{print $9}' | awk '$1>0' \
| sort -n | uniq -c | awk '{print $2, $1}' > fragment_sizes.tsv
For CUT&Tag: 25-75 bp characteristic; fragments < 25 bp are Tn5 self-tagmentation noise (see cut-and-run-tag).
QC Metric Battery with ENCODE Thresholds
| Metric | Tool | TF threshold | Histone threshold | Source / rationale |
|---|---|---|---|---|
| FRiP (Fraction of Reads in Peaks) | bedtools / pysam / featureCounts | ≥ 0.01 minimum, > 0.05 ideal | ≥ 0.05, > 0.20 ideal; > 0.15 for H3K4me3 | Landt 2012; ENCODE flags experiments with FRiP < 1% |
| NSC (Normalized Strand Cross-correlation) | phantompeakqualtools | > 1.05 marginal, > 1.10 ideal | > 1.05 | Landt 2012; min = 1 (no enrichment); ratio of fragment-length CC to background |
| RSC (Relative Strand Cross-correlation) | phantompeakqualtools | > 0.8 marginal, > 1.0 ideal | > 0.8 | Landt 2012; ratio of (fragment - background) / (phantom - background) |
| QualityTag | phantompeakqualtools | ≥ 0 acceptable, 1-2 ideal | ≥ 0 | Composite based on NSC/RSC; -2 to 2 scale |
| NRF (Non-Redundant Fraction) | unique_pos / total | > 0.8 | > 0.8 | ENCODE; < 0.5 severe PCR bottleneck |
| PBC1 (M1 / Mdistinct) | bedtools / pysam | > 0.8 | > 0.8 | ENCODE; fraction of singly-occupied positions |
| PBC2 (M1 / M2) | bedtools / pysam | > 3 | > 3 | ENCODE; ratio of singletons to doubletons |
| JS distance (plotFingerprint) | deepTools | > 0.3 | > 0.05 (broad) to > 0.3 (narrow) | Distance between cumulative signal curves IP vs Input |
| AUC (plotFingerprint) | deepTools | < 0.6 | 0.6-0.9 | Input = ~0.5; lower AUC = more enrichment concentrated |
| Synthetic JS (plotFingerprint) | deepTools | Should ≈ measured JS | — | Sanity check vs simulated null |
| Replicate Spearman correlation | deepTools multiBamSummary / plotCorrelation | > 0.8 (true reps) | > 0.8 (true reps), > 0.6 (broad) | Replicates should correlate more than cross-condition |
| Read count per replicate | samtools flagstat | ≥ 20M unique mapped | 20M (narrow histone), 40-60M (broad histone) | ENCODE 2012 |
Practical operational rule: Compute the full battery. Reject any sample failing FRiP OR antibody validation OR fragment-size sanity check, regardless of other metrics. Failing one of NSC/RSC alone with strong FRiP can sometimes be rescued for narrow-peak biology; broad histones are more forgiving on NSC.
Hyper-ChIPable Region Detection
Teytelman 2013 (PNAS): untagged GFP, no antibody, or non-existent targets all produce "binding" signal at highly-transcribed loci (rRNA, tRNA, histone gene clusters, snoRNA hosts, mtDNA, abundant housekeeping genes). ENCODE blacklist v2 (Amemiya 2019) catches repeat-driven artifacts but NOT these hyper-ChIPable transcribed regions.
Detection:
# Top 1% input signal as cell-type-specific custom blacklist
multiBigwigSummary BED-file -b input.bw -o input_signal.npz \
--BED genes.bed --outRawCounts input_per_gene.tsv
awk 'NR > 1' input_per_gene.tsv | sort -k4,4nr | head -n $(($(wc -l < input_per_gene.tsv) / 100)) \
> hyper_chipable.bed
# Intersect peaks against this list; flag peaks falling in hyper-ChIPable regions
bedtools intersect -a peaks.narrowPeak -b hyper_chipable.bed -u > suspicious_peaks.bed
Disprove a suspicious peak: Required for any claim at rRNA loci, tRNA clusters, HIST1/2 clusters, mitochondrial DNA:
- Motif enrichment at peak (artifact has no enrichment)
- KO/KD signal loss at peak (artifact persists)
- Untagged-protein control ChIP shows no signal at this locus
Many "novel binding" claims at the rDNA repeat, mtDNA, and HIST1 cluster are spurious artifacts.
Computing the Battery
FRiP
total_reads=$(samtools view -c -F 260 chip.bam)
reads_in_peaks=$(bedtools intersect -a chip.bam -b peaks.narrowPeak -u | samtools view -c -)
frip=$(echo "scale=4; $reads_in_peaks / $total_reads" | bc)
NSC / RSC / fragment length (phantompeakqualtools)
Rscript run_spp.R -c=chip.bam -savp=qc/chip_cc.pdf -out=qc/chip_cc.txt
# Output columns: filename | numReads | estFragLen | corr_estFragLen |
# phantomPeak | corr_phantomPeak | argmin_corr | min_corr |
# NSC | RSC | QualityTag
Library complexity
# NRF
total=$(samtools view -c -F 260 chip.bam)
unique=$(samtools view -F 260 chip.bam | awk '{print $1, $3, $4}' | sort -u | wc -l)
nrf=$(echo "scale=4; $unique / $total" | bc)
# PBC1, PBC2 (singletons vs distinct positions vs doubletons)
samtools view -F 260 chip.bam | awk '{print $3":"$4}' | sort | uniq -c \
| awk '{
if ($1 == 1) m1++;
if ($1 == 2) m2++;
mdist++;
} END {
print "M1:", m1; print "M2:", m2; print "Mdistinct:", mdist;
print "PBC1:", m1/mdist; print "PBC2:", m1/m2
}'
deepTools plotFingerprint
plotFingerprint \
-b chip.bam input.bam \
--labels ChIP Input \
-o qc/fingerprint.pdf \
--outRawCounts qc/fingerprint_counts.tab \
--outQualityMetrics qc/fingerprint_qc.txt
# Inspect qc/fingerprint_qc.txt: AUC, JS distance, synthetic JS, X-intercept
# Good ChIP: AUC < 0.6 (TF), JS > 0.3 (TF); Input near diagonal (AUC ~ 0.5)
Replicate Spearman correlation
multiBamSummary bins -b rep1.bam rep2.bam rep3.bam input.bam \
--binSize 10000 -o results.npz
plotCorrelation -in results.npz --corMethod spearman \
--whatToPlot heatmap --plotNumbers -o corr.pdf \
--outFileCorMatrix corr_matrix.tab
# Replicates: > 0.8 (narrow), > 0.6 (broad)
# Cross-condition reps should correlate less than within-condition
ChIPQC R package
library(ChIPQC)
samples <- read.csv('samples.csv')
qc <- ChIPQC(samples, annotation = 'hg38')
ChIPQCreport(qc, reportFolder = 'ChIPQCreport')
# Generates the full ENCODE battery report per sample in one call
ChIPQC remains Bioconductor-maintained but mature; phantompeakqualtools is the canonical NSC/RSC source.
IDR and Replicate Consistency Rules
For TFs: signal-ranked IDR with Nself/Nt consistency check; see chip-seq/peak-calling for full ENCODE workflow. Key thresholds:
- True replicate IDR threshold: 0.05
- Pseudoreplicate IDR threshold: 0.10 (per-rep self-consistency)
- Nself/Nt rule:
max(N1self, N2self) / min(N1self, N2self) ≤ 2ANDmax(Nt, max(Nself)) / min(Nt, min(Nself)) ≤ 2. Failing both ratios rejects the library.
For histones: naive overlap with ≥ 40% reciprocal overlap (ENCODE default; commonly misquoted as 50%). IDR is too conservative for histone signal dynamic range.
ENCODE 3 vs ENCODE 4 Thresholds (unchanged for most QC)
| Metric | ENCODE 3 | ENCODE 4 |
|---|---|---|
| FRiP minimum | 1% | 1% (unchanged) |
| NSC threshold | > 1.05 | > 1.05 (unchanged) |
| RSC threshold | > 0.8 | > 0.8 (unchanged) |
| NRF threshold | > 0.8 | > 0.8 (unchanged) |
| Blacklist | v1 | v2 (Amemiya 2019) |
| Read depth (TF) | ≥ 20M unique mapped | ≥ 20M unchanged |
| Read depth (broad histone) | ≥ 40M | 40-60M recommended |
Most QC thresholds are stable across ENCODE versions; blacklist update is the main practical change.
Per-Tool Failure Modes
phantompeakqualtools / SPP -- R version incompatibility
Trigger: Running with R ≥ 4.0.
Mechanism: spp R package has unmaintained Boost / Rcpp dependencies; some shifts produce NaN cross-correlation values.
Symptom: NSC = NaN, RSC = NaN, or fragment length = 0 in output.
Fix: Pin to R 3.6 + spp 1.16 via conda env; OR use the kundajelab/phantompeakqualtools fork (current); OR substitute deepTools plotFingerprint for enrichment QC and macs3 predictd for fragment length.
deepTools plotFingerprint -- Wrong baseline assumption for broad marks
Trigger: Interpreting JS distance with TF threshold (> 0.3) on broad histone mark.
Mechanism: Broad marks have less concentrated signal; JS distance is naturally lower (0.05-0.15 for H3K27me3) without indicating bad ChIP.
Symptom: Reports "failed JS distance" for high-quality broad-mark ChIP.
Fix: Use mark-specific thresholds: > 0.3 for TFs and sharp histones; > 0.05 for broad histones; check AUC instead (0.6-0.9 for broad; < 0.6 for TF/sharp).
FRiP -- Computed before vs after blacklist filtering
Trigger: Calling FRiP from peak file pre- vs post-blacklist.
Mechanism: Hyper-ChIPable regions inflate "reads in peaks" because most reads at those loci are artifacts.
Symptom: FRiP looks great (>15%) but most of it is rRNA / mtDNA reads.
Fix: Apply blacklist + custom hyper-ChIPable filter BEFORE computing FRiP; or report both raw and filtered FRiP.
NRF / PBC -- Computed after deduplication
Trigger: Running NRF on a MarkDuplicates-filtered BAM.
Mechanism: Library complexity metrics measure PCR redundancy; if duplicates are already removed, NRF = 1.0 by construction (uninformative).
Symptom: NRF reports 0.99-1.0; metric is meaningless.
Fix: Compute NRF / PBC1 / PBC2 on the PRE-deduplication BAM. ENCODE-compliant pipeline: filter -> MarkDuplicates (don't remove) -> compute NRF -> filter out duplicates -> call peaks.
IDR -- Wrong rank column
Trigger: Sorting narrowPeak by signalValue (column 7) for IDR.
Mechanism: MACS signalValue scales with pile-up intensity which differs between libraries of different depth; rank correlation breaks.
Symptom: IDR returns 0 reproducible peaks despite good replicate Spearman correlation.
Fix: Sort by p-value (-k8,8nr), pass --rank p.value to IDR. ENCODE convention.
ChIPQC -- Default annotation mismatch
Trigger: Using annotation = 'hg19' on hg38-aligned data.
Mechanism: ChIPQC computes feature-context enrichment from the specified annotation; mismatch silently corrupts enrichment metrics.
Symptom: Promoter / 5'UTR / 3'UTR enrichments look wrong; replicate report metrics drift.
Fix: Match annotation to the genome the BAMs were aligned to; for custom genomes pass a TxDb object explicitly.
Reconciliation: When Metrics Disagree
| Pattern | Likely cause | Action |
|---|---|---|
| Good FRiP, bad NSC | High background but real enrichment | Acceptable for broad marks; for TFs, check phantompeakqualtools fragment length is reasonable |
| Good NSC, bad FRiP | Strong cross-correlation signal but few peaks pass q-value | Library shallow OR peak caller threshold too strict; try -p 1e-2 |
| Good FRiP and NSC, bad replicate correlation | Real biology + replicate-specific batch effect | Check sample swap; check sequencing batch; consider PCA |
| Good Rep1, bad Rep2 | One replicate failed | Drop Rep2 + repeat; do NOT average metrics |
| All metrics fail | Antibody or fragmentation failure | Re-validate antibody (KO/KD); inspect fragment-size distribution; do not proceed |
| FRiP excellent at rRNA/mtDNA | Hyper-ChIPable artifact dominance | Build custom blacklist; recompute |
Operational rule for proceeding with downstream analysis: Require (1) antibody validated, (2) fragment-size distribution sane, (3) FRiP, NSC, RSC pass ENCODE thresholds, (4) Nself/Nt rule satisfied for TFs OR naive overlap concordance for histones, (5) hyper-ChIPable artifacts identified and either filtered or flagged.
Common Errors
| Error / symptom | Cause | Solution |
|---|---|---|
Sequence chrM not found (multi-tool) |
chrM removed from BAM but kept in genome FASTA | Match chromosome naming convention; consistently include or exclude chrM |
| phantompeakqualtools hangs / OOM | Default tag chunking on deep libraries | Subsample to 15-25M reads (samtools view -s) before running |
| plotFingerprint blank or near-diagonal | Input control mislabeled as ChIP | Verify sample labels; AUC ~ 0.5 = Input-like signal |
| IDR runs but Nself ratio always > 2 | One pseudoreplicate dominates due to seed | Use sufficiently different seeds (-s 1.5 and -s 2.5) |
| ChIPQC report missing peaks | samples.csv path columns wrong | Verify bamReads / Peaks paths; ChIPQC fails silently on missing files |
| Replicate Spearman > 0.95 | Technical (not biological) replicates | Treat as one sample; do not report as biological replicates |
References
- Landt SG et al 2012 Genome Res 22:1813 (ENCODE/modENCODE QC guidelines, IDR Nself rule)
- Kharchenko PV et al 2008 Nat Biotechnol 26:1351 (SPP, NSC/RSC framework)
- Li Q et al 2011 Ann Appl Stat 5:1752 (IDR)
- Marinov GK et al 2014 G3 4:209 (large-scale ChIP-seq QC comparison)
- Teytelman L et al 2013 PNAS 110:18602 (hyper-ChIPable regions)
- Amemiya HM et al 2019 Sci Rep 9:9354 (ENCODE blacklist v2)
- Ramírez F et al 2016 Nucleic Acids Res 44:W160 (deepTools)
- Carroll TS et al 2014 Front Genet 5:75 (ChIPQC framework)
- Diaz A et al 2012 Stat Appl Genet Mol Biol 11:Article 9 (SES normalization / fingerprint-style QC)
- Park PJ 2009 Nat Rev Genet 10:669 (foundational review)
- Rothbart SB et al 2015 Mol Cell 59:502 (histone antibody specificity database)
Related Skills
- chip-seq/peak-calling - Use QC metrics to decide whether to proceed with peak calling
- chip-seq/cut-and-run-tag - CUT&RUN/CUT&Tag QC differs (spike-in % aligned, fragment-size signatures)
- chip-seq/spike-in-normalization - QC for spike-in carryover and Drosophila read depth
- chip-seq/differential-binding - Replicate concordance required before differential testing
- atac-seq/atac-qc - Parallel QC for ATAC-seq (no input control, different thresholds)
- alignment-files/bam-statistics - General BAM-level QC
- alignment-files/duplicate-handling - MarkDuplicates before NRF computation