| name | bio-clip-seq-clip-peak-calling |
| description | Call protein-RNA binding sites from CLIP-seq BAM with CLIPper, PureCLIP, Skipper, Piranha, omniCLIP, CTK, CLAM, or Paraclu. Use when choosing between coverage-based, HMM-based, beta-binomial window-based, and crosslink-site-based peak callers; applying ENCODE eCLIP thresholds (log2 IP/SMInput >= 3, -log10 p >= 3); deciding when SMInput is mandatory; or reconciling peak-set discordance between callers for the same RBP. |
| origin | openai4s |
| category | bioskills/clip-seq |
| metadata | {"tool_type":"cli","primary_tool":"CLIPper","third_party":{"name":"GPTomics/bioSkills","repository":"https://github.com/GPTomics/bioSkills","commit":"d91ed3d563019e649dc854c56ccd62551359488a","license":"MIT"}} |
Version Compatibility
Reference examples tested with: CLIPper 2.0+, PureCLIP 1.3.1+, Piranha 1.2.1+, omniCLIP 0.2.0+, CTK 1.1.4+, CLAM 1.2+, Paraclu 9+, Skipper (commit 2023.05+), MACS3 3.0+, bedtools 2.31+, samtools 1.19+, idr 2.0.4+.
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package> then help(module.function) to check signatures
- CLI:
<tool> --version then <tool> --help to confirm flags
If code throws unexpected errors, introspect the installed binary and adapt the example to match the actual CLI rather than retrying. PureCLIP 2.x changed several flag names; Skipper is distributed as a Snakemake workflow with frequently-evolving paths.
CLIP-seq Peak Calling
"Call protein-RNA binding sites from my deduplicated CLIP BAM" -> Identify regions where read pile-up (and, for iCLIP/eCLIP, single-nucleotide truncations) exceed background from a size-matched input (SMInput) control. The choice of peak caller depends on (a) the CLIP variant (HITS-CLIP, iCLIP, eCLIP, PAR-CLIP), (b) whether SMInput is available, (c) the RBP binding mode (narrow motif vs broad zones vs repeat-binding), and (d) the goal (publication-comparable ENCODE peaks vs single-nucleotide crosslink sites vs high-recall site lists).
- CLI (ENCODE eCLIP canonical):
clipper -b dedup.bam -s hg38 -o peaks.bed --save-pickle --FDR-alpha 0.05 --superlocal then eclip-norm peaks.bed -i sminput.bam for log2 fold-change against SMInput (--FDR-alpha is the CLIPper flag for the FDR cutoff; older docs sometimes shorten to --FDR)
- CLI (single-nucleotide crosslink sites, iCLIP/eCLIP):
pureclip -i dedup.bam -bai dedup.bam.bai -g genome.fa -ibam sminput.bam -ibai sminput.bam.bai -o sites.bed -or regions.bed -nt 8 -dm 8
- CLI (high-recall, beta-binomial windowed; needs SMInput):
Skipper Snakemake workflow with config matching cell type and SMInput BAM
- CLI (no SMInput, no truncation):
Piranha -b 50 -p 0.01 -d ZeroTruncatedNegativeBinomial -s -o peaks.bed dedup.bam (Piranha takes the BAM as a positional argument, not via -s)
- CLI (CIMS/CITS single-nt from CTK):
tag2cluster.pl dedup.bed cluster.bed --multi-tag-method coverage; then bedExtractCIMS.pl cluster.bed cims.bed
- CLI (multi-mapper rescue for repeat-binding RBPs):
CLAM peakcaller -i unique.bam multimap.bam -o clam_out_dir/ --gtf gencode.gtf (CLAM peakcaller writes peaks into an OUTPUT DIRECTORY, not a single file)
The ENCODE eCLIP gold standard for "stringent" peaks is: log2(IP / SMInput) >= 3 AND -log10(p-value) >= 3. "Lenient" peaks use log2 >= 1 AND -log10 >= 2. Both filters operate on CLIPper peak output normalized against SMInput. Without SMInput, neither stringency level can be reproduced - the algorithm has no background term.
Algorithmic Taxonomy
| Caller | Model | Resolution | SMInput required | Strength | Fails when |
|---|
| CLIPper (Yeo) | Poisson with 500 bp local lambda, cubic-spline interpolation | Peak (10-500 nt) | Not for calling; required for ENCODE normalization | ENCODE eCLIP standard; reproducible against published ENCODE peak sets | Assumes most reads not from binding; fails when IP signal dominates a gene; sensitive to highly expressed transcripts |
| PureCLIP (Krakau 2017) | Non-homogeneous HMM jointly modeling enrichment + truncation + sequence biases | Single-nucleotide CL + broad region | Optional via -ibam; recommended | Single-nt resolution; only caller that explicitly models the iCLIP truncation pattern | Misses broad binding zones; very focal (low recall on broad-binding RBPs in the Boyle 2023 benchmark) |
| Skipper (Boyle 2023) | GC-stratified beta-binomial, 100 bp feature-respecting windows | Window (~100 nt) | Mandatory | 210-320% more sites than CLIPper; 8x faster; properly normalizes against input | Loses single-nt resolution; relatively new (2023); fewer published peak sets to compare |
| Piranha (Smith lab) | Zero-truncated negative binomial regression with optional covariates | Bin (50-200 nt) | Optional; pass as covariate | Mature, widely cited, handles count overdispersion | Biased toward high-expression transcripts; convergence fails with large covariate values (use -l log-space) |
| omniCLIP (Drewe-Boss 2018) | Non-homogeneous HMM with Dirichlet-multinomial of variants | Peak | Required | Models replicate variance; integrates background; can call peaks on any CLIP variant | Slow on deep libraries; blind to mitochondrial transcripts (misses chrM windows for FASTKD2) |
| CTK CIMS/CITS (Shah 2017) | Empirical FDR on crosslink-induced mutations or truncations | Single-nucleotide | No (uses background mutation rate from non-bound transcripts) | Single-nt resolution; works on HITS-CLIP deletions, PAR-CLIP T->C, iCLIP truncations | Empirical FDR less principled than HMM/beta-binomial; perl-based pipeline harder to integrate |
| CLAM peakcaller (Zhang & Xing 2017) | EM-assigned multi-mapper count + Piranha-like negative binomial | Peak | Optional | Only solution for repeat-binding RBPs; 10-30% additional sites in repeats |
Methodology evolves; verify the current ENCODE eCLIP standard operating procedure (encodeproject.org/eclip) and the nf-core/clipseq pipeline configuration before locking on a single caller. The 2023 Skipper benchmark (Boyle Cell Genomics) is the most recent comprehensive comparison and is the rationale for many recent eCLIP reanalyses.
Critical Choice: Coverage-Based vs Crosslink-Site-Based vs Window-Based
Three fundamentally different statistical frameworks:
Coverage-based (CLIPper, Piranha, MACS3, Paraclu): Tally reads in a window; significance from local Poisson or negative binomial. Produces multi-nt peaks. Best when binding zones are broader than the read footprint (PUM2 3' UTR, HuR ARE elements).
Crosslink-site-based (PureCLIP, CTK CIMS/CITS, PARalyzer): Identify single nucleotides enriched in truncations (iCLIP/eCLIP) or specific mutations (PAR-CLIP T->C, HITS-CLIP deletions). Produces single-nt sites that can be aggregated into footprints. Best when single-nt resolution is essential (motif registration with mCross; allele-specific binding).
Window-based (Skipper): Tile transcriptome a priori into fixed-size feature-respecting windows; test each window's IP/IN ratio with beta-binomial. Produces window-level calls. Best when SMInput is available and the goal is high-recall, comparable-across-RBPs site sets.
| Goal | Recommended caller | Why |
|---|
| Reproduce ENCODE published peaks | CLIPper + IP/SMInput normalization | The Yeo lab pipeline is the canonical reference |
| Maximum sensitivity, modern statistics, SMInput available | Skipper | 210-320% more sites; explicit input normalization |
| Single-nucleotide crosslink-site map (motif registration, ASB) | PureCLIP (HMM) or CTK CITS (empirical) | True single-nt resolution |
| Repeat-binding RBP (Alu, LINE, LTR) | STAR multi-mapper + CLAM peakcaller | Only solution that uses multi-mappers |
| No SMInput control | Piranha or PureCLIP with no -ibam | Both work without input but lose specificity |
| PAR-CLIP T->C signature | PARalyzer or CTK CIMS (-substitution) | Designed for the T->C signal |
| HITS-CLIP deletion signature | CTK CIMS (-deletion) | Designed for the deletion signal |
| Custom statistical model needed | omniCLIP | Most flexible HMM among the options |
| Online interactive analysis | Galaxy CLIP-Explorer or PIPE-CLIP | Web interface |
ENCODE eCLIP Stringency Thresholds
The Van Nostrand et al. ENCODE eCLIP standards define two stringency levels for CLIPper peaks normalized against SMInput:
| Stringency | log2(IP / SMInput) | -log10(p-value) | Use case |
|---|
| Stringent (publication) | >= 3 | >= 3 | High-confidence binding sites; differential analysis; motif discovery |
| Lenient (discovery) | >= 1 | >= 2 | Catalogue of all enriched windows; sensitive analyses |
Both thresholds are applied to the IDR-passing reproducible peak set. ENCODE requires:
-
= 2 biological replicates
-
= 1M unique fragments per replicate (or saturated peak detection)
- IDR rescue ratio and self-consistency ratio both < 2
- Narrow-binding RBPs: FRiP >= 0.005 (atypical-binding RBPs exempt)
clipper -b dedup.bam -s hg38 -o peaks.bed --save-pickle --FDR-alpha 0.05 --superlocal
python overlap_peakfi_with_bam_PE.py peaks.bed dedup.bam sminput.bam dedup.bam.readnum.txt sminput.bam.readnum.txt peaks.normed.bed
python compress_l2foldenrpeakfi_for_replicate_overlapping_bedformat.py peaks.normed.bed peaks.compressed.bed
awk 'BEGIN{FS=OFS="\t"} $4 >= 3 && $5 >= 3' peaks.compressed.bed > peaks.stringent.bed
awk 'BEGIN{FS=OFS="\t"} $4 >= 1 && $5 >= 2' peaks.compressed.bed > peaks.lenient.bed
The Yeo lab scripts (overlap_peakfi_with_bam_PE.py, compress_l2foldenrpeakfi_for_replicate_overlapping_bedformat.py) live in the eclip-pipeline repository; they implement the exact log2 fold-change computation used for ENCODE data downloads.
Per-Caller Failure Modes
CLIPper -- High-expression transcript bias
Trigger: RBP that binds rare transcripts (snoRNAs, tRNAs, mitochondrial mRNAs) such as TROVE2 (Y RNA), NSUN2 (tRNA), or FASTKD2 (chrM).
Mechanism: CLIPper's Poisson local-lambda model assumes only a minority of reads come from binding. For rare-transcript binders, the IP reads ARE the majority signal on that transcript; the model treats them as background.
Symptom: Per-transcript peak count plummets compared to qualitatively-visible IP signal; chrM peaks called by Skipper but missed by CLIPper for FASTKD2.
Fix: Use Skipper for rare-transcript binders (beta-binomial against SMInput respects the actual IP/IN ratio independently of local lambda). Or pre-restrict CLIPper to the target transcript with --gene custom.bed.
CLIPper -- Requires SMInput downstream
Trigger: Submitting CLIPper output as "peaks" without IP/SMInput log2 normalization.
Mechanism: CLIPper's own p-value is uncorrected for SMInput background. ENCODE peak BED files distributed on the portal are CLIPper + SMInput log2 normalization combined.
Symptom: Peak count from the analysis is 5-10x higher than ENCODE values for the same RBP; the peak set includes obvious housekeeping-gene noise.
Fix: Always normalize CLIPper output against SMInput. The Yeo lab scripts (overlap_peakfi_with_bam_PE.py + compress_l2foldenrpeakfi_for_replicate_overlapping_bedformat.py) produce the canonical ENCODE-style peak.
PureCLIP -- Too focal; misses broad binding zones
Trigger: RBP with broad binding mode (PUM2 in 3' UTR clusters; SR proteins across exonic enhancer regions); using PureCLIP and disappointed.
Mechanism: PureCLIP's HMM emits single-nt crosslink-site state at high stringency. In the Boyle 2023 Skipper benchmark, PureCLIP was highly focal with low recall on broad-binding RBPs (few true-positive windows).
Symptom: Site count 100x lower than expected; sites cluster within known binding regions but vast majority of region is "background" in PureCLIP output.
Fix: Use PureCLIP for single-nt CL maps (motif registration, ASB) but pair with CLIPper or Skipper for the broader binding-site list. PureCLIP's -or regions file gives broader output but is still focal compared to CLIPper.
Piranha -- Top-expression-decile bias
Trigger: Highly expressed transcript (GAPDH, ACTB, rRNA-flanking) appears in most-significant Piranha peaks even when RBP biology is elsewhere.
Mechanism: ZTNB regression weights peak significance by absolute count, not relative enrichment. Genes with 10x baseline expression dominate the top of the peak list.
Symptom: Top-100 Piranha peaks include housekeeping genes; motif enrichment in top peaks is weak; functional GO term analysis of peak-bearing genes returns generic "cellular metabolism."
Fix: Use Piranha with SMInput as a covariate (-c sminput_counts.bed -l) so the regression accounts for input pile-up. Or switch to Skipper for principled input normalization.
Piranha -- Convergence failure with covariates
Trigger: -c rna_seq.bed for expression normalization; large per-bin RNA-seq counts (> 10000).
Mechanism: ZTNB optimization fails on extreme covariate values; the iterative algorithm diverges.
Symptom: "Maximum iterations reached" or "Singularity in regression" error; or output BED file empty.
Fix: Pass -l to convert covariates to log-space; or pre-filter covariate BED to remove top-1% outlier bins; or switch to Skipper which handles input normalization internally.
omniCLIP -- Mitochondrial transcript blind spot
Trigger: Mitochondrial RBP (FASTKD2, LRPPRC) submitted to omniCLIP.
Mechanism: omniCLIP's HMM is trained on autosomal/X transcripts; chrM has different background statistics that the model treats as outlier (or excludes if blacklisted).
Symptom: chrM peaks return 0; FASTKD2 peak file has no peaks at all.
Fix: Use Skipper for chrM-binding RBPs (GC-stratified beta-binomial is per-bin and indifferent to chromosome). Or call peaks on chrM separately with PureCLIP.
CTK CIMS -- HITS-CLIP only; iCLIP/eCLIP misuse
Trigger: CTK CIMS (-mutation flag) applied to iCLIP/eCLIP data.
Mechanism: iCLIP/eCLIP use truncation (RT stops at adduct), not mutations. CIMS expects deletions/substitutions inside the read; CITS is the truncation-based companion.
Symptom: CIMS returns very few sites (mutation rate of CL is ~3-7% for HITS-CLIP, but only ~1-2% for iCLIP since most reads truncate before reaching the adduct).
Fix: For iCLIP/eCLIP, use CTK CITS (tag2cluster.pl ... -cs5 5 truncation-mode). For HITS-CLIP and PAR-CLIP, CIMS is correct (HITS deletions, PAR T->C).
CLAM peakcaller -- Multi-mapper BAM absent
Trigger: Ran STAR with --outFilterMultimapNmax 1 then tried CLAM; CLAM fails or returns identical output to Piranha.
Mechanism: CLAM's EM rescue requires the multi-mapper BAM from STAR (--outFilterMultimapNmax 100 --outSAMmultNmax -1). Without it, CLAM falls back to unique-only Piranha-style peak calling.
Symptom: CLAM output looks identical to Piranha; repeat peaks not rescued.
Fix: Re-align with multi-mapper-aware STAR parameters (see clip-seq/clip-alignment). Verify the multi-mapper BAM has alignments at non-unique positions before running CLAM.
MACS3 callpeak -- Wide peaks miss footprint
Trigger: MACS3 used because the user is familiar from ATAC/ChIP work.
Mechanism: MACS3 model is for DNA-protein binding at ~100-500 nt scale; CLIP-seq RBP footprints are 8-30 nt. MACS3 wide peaks (300+ nt) merge multiple distinct binding sites.
Symptom: MACS3 peak count is much lower than CLIPper/Skipper; mean peak width >> 100 nt; multiple known motif instances inside one MACS peak.
Fix: Use CLIP-specific callers. If MACS3 is forced (institutional pipeline), pass --nomodel --shift -1 --extsize 50 for narrower peaks and accept the limitation.
IDR for CLIP-seq
IDR (Li 2011) measures reproducibility of peak rankings across biological replicates. ENCODE eCLIP convention is per-rep + pooled + pseudoreplicates, identical to the ChIP-seq IDR pattern. The CLIP-specific consideration: rank by signalValue (column 7) NOT by score (column 5), because CLIPper's score is sparse and tied across many peaks.
sort -k7,7nr rep1_peaks.compressed.bed > rep1.sorted
sort -k7,7nr rep2_peaks.compressed.bed > rep2.sorted
idr --samples rep1.sorted rep2.sorted \
--input-file-type bed --rank 7 \
--output-file idr.out --idr-threshold 0.05 \
--plot --log-output-file idr.log
ENCODE IDR rules for eCLIP:
- Nt (true replicates) and Nself (pseudoreplicates): max(Nt, Nself) / min(Nt, Nself) <= 2 -> pass
- Both ratios > 2 -> library rejected
- IDR threshold 0.05 for true reps; 0.10 for pseudoreplicates
Decision Tree by Scenario
| Scenario | Caller + parameters | Why |
|---|
| Standard eCLIP with SMInput, ENCODE-comparable | CLIPper + SMInput log2 norm + IDR | Reproducible against ENCODE peak files |
| Standard eCLIP with SMInput, maximum sensitivity | Skipper Snakemake workflow | 210-320% more sites, beta-binomial input-norm |
| iCLIP/iCLIP2, want single-nt CL map | PureCLIP + SMInput (or empty bam if no SMI) | HMM jointly models enrichment + truncation |
| HITS-CLIP, want CIMS deletions | CTK parseAlignment.pl + tag2cluster.pl + bedExtractCIMS.pl | Empirical FDR on deletion-induced mutations |
| PAR-CLIP, T->C signal | PARalyzer or CTK CIMS -substitution T C | Designed for the T->C signature |
| Repeat-binding RBP (MATR3, LINE-1) | CLAM peakcaller on multi-mapper BAM | Only solution that recovers repeat peaks |
| No SMInput, mostly hopeless | Piranha -d ZeroTruncatedNegativeBinomial or PureCLIP w/o -ibam | Lose ENCODE comparability but get a peak set |
| Mitochondrial RBP (FASTKD2) | Skipper (window-based, chrM-friendly) | omniCLIP/CLIPper miss chrM |
| Highly multiplexed (SPIDR) | Custom Snakemake; no single-tool solution | Each barcode's reads are deep enough for CLIPper |
| Long-read CLIP (dirCLIP) | Custom analysis from BAM; long-read tools not yet mature | Isoform-resolved binding-site calls |
| Need maximum precision for motif analysis | PureCLIP (single-nt) + mCross downstream | mCross requires registered CL positions |
| Replicates with unequal library complexity (>2x diff in unique fragments) | Skipper (more robust to depth imbalance) OR samtools view -s down-sample to common depth then CLIPper + IDR | Skipper's GC-stratified beta-binomial handles per-sample depth; CLIPper without down-sampling lets the deeper replicate dominate joint analysis |
Reconciliation: When Callers Disagree
| Pattern | Likely cause | Action |
|---|
| Skipper >> CLIPper site count | Skipper better recovers low-abundance and rare-transcript binders | Trust Skipper for rare transcripts; trust CLIPper for ENCODE-comparable counts |
| PureCLIP << CLIPper | PureCLIP is single-nt focal; CLIPper is broad peak | Both correct; report at the resolution the downstream analysis needs |
| Piranha top peaks dominated by housekeeping | No input normalization | Add SMInput as -c covariate or switch to Skipper |
| CLAM > Piranha by 10-30% | CLAM rescued multi-mappers in repeats | Trust CLAM if RBP biologically binds repeats |
| omniCLIP wider peaks than CLIPper | HMM smoothes binding state across nearby positions | Both correct; choose by downstream analysis needs |
| Per-rep CLIPper calls peak; pooled does not | Replicates inconsistent; one rep dominates | Inspect with IGV; trust IDR-passing peaks only |
| MACS3 < CLIPper peak count | MACS3 wide peaks merge multiple CLIP sites | Use CLIP-specific caller |
| FASTKD2 chrM peaks: Skipper finds; CLIPper / omniCLIP find none | Coverage-based callers blind to chrM lambda | Trust Skipper for organelle-binding RBPs |
| chimeric eCLIP peaks for snoRNA: standard tools find few | snoRNA-targeting eCLIP needs custom processing | Use VanNostrandLab/snoRNA-chimeric pipeline |
Operational rule for high-confidence reporting: Require a peak to pass (a) IDR <= 0.05 on true replicates, (b) log2(IP/SMInput) >= 3 AND -log10 p >= 3 (ENCODE stringent), (c) overlap with at least one independent caller within 100 nt. For motif analysis, additionally require PureCLIP single-nt sites within the peak. For ASB, require WASP-filtered alignment + PureCLIP CL sites overlapping heterozygous SNPs.
Strand-Specific Peak Calling
CLIP libraries are strand-specific by design. Most callers handle strands correctly when the BAM is stranded (read flags 99/147/83/163 for paired). If a caller bug or unstranded library forces manual split:
samtools view -h -b -F 16 dedup.bam > plus.bam
samtools index plus.bam
samtools view -h -b -f 16 dedup.bam > minus.bam
samtools index minus.bam
clipper -b plus.bam -s hg38 -o peaks_plus.bed
clipper -b minus.bam -s hg38 -o peaks_minus.bed
cat peaks_plus.bed peaks_minus.bed | sort -k1,1 -k2,2n > peaks_stranded.bed
For paired-end CLIP, mate orientation determines strand: RF (R1 reverse) means R2 5' is the truncation = CL site -1 on plus-strand transcripts. ENCODE eCLIP convention: read 2 of pair is the truncation-bearing read.
Multi-Mapper Rescue with CLAM (Repeat Binders)
samtools sort -o multimap.bam aligned_multimap.bam
samtools index multimap.bam
CLAM preprocessor -i multimap.bam -o clam_out/ --read-tagger-method median
CLAM realigner -i clam_out/unique.sorted.bam -o clam_out/ --winsize 50 --max-tags 0
CLAM peakcaller -i clam_out/unique.sorted.bam clam_out/realigned.sorted.bam \
-o clam_peaks.bed -p 8 --gtf gencode.v38.annotation.gtf
CLAM rescues 10-30% additional peaks in repeat-rich regions. The trade-off: peak coordinates in repeat instances are probabilistic (single best from EM), so motif analysis on CLAM repeat peaks requires careful interpretation.
Quality Metrics for Peak Sets
import pandas as pd
def peak_qc(peaks_bed):
peaks = pd.read_csv(peaks_bed, sep='\t', header=None,
names=['chrom','start','end','name','score','strand'])
peaks['width'] = peaks['end'] - peaks['start']
return {
'n_peaks': len(peaks),
'mean_width': peaks['width'].mean(),
'median_width': peaks['width'].median(),
'width_5p_95p': (peaks['width'].quantile(0.05), peaks['width'].quantile(0.95)),
'chroms_with_peaks': peaks['chrom'].nunique(),
'peaks_chrM': (peaks['chrom'] == 'chrM').sum()
}
| Metric | Expected | Interpretation |
|---|
| n_peaks (CLIPper stringent) | 5k - 100k | <5k = under-IP or stringency too high; >>100k = noisy library |
| Mean peak width (CLIPper) | 40-200 nt | Wider = caller over-merging; narrower = under-coverage |
| Peak width 5-95% range | 20-500 nt | Tight range = consistent peaks; wide = mixed sharp + broad |
| FRiP (fraction reads in peaks) | >= 0.005 | ENCODE narrow-binding RBP minimum; many RBPs higher |
| chrM peaks | 0 unless mt-RBP | FASTKD2, LRPPRC expected to have chrM enrichment |
| TPM-rank distribution | Spread across deciles | Concentrated in top decile = caller has expression bias (Piranha symptom) |
Common Errors
| Error / symptom | Cause | Solution |
|---|
| CLIPper "no peaks found" | BAM not sorted/indexed; gene annotation missing | samtools sort && index; verify -s hg38 (or --gene custom.bed) |
| CLIPper out-of-memory on 50M BAM | --save-pickle keeps intermediates in RAM | Remove --save-pickle; or use machine with > 64 GB |
| PureCLIP slow (>24h) | -iv interval file missing | Restrict to one chromosome with -iv chr1 for testing; provide GTF |
| Piranha returns no peaks | ZTNB convergence failed silently | Add -l; or reduce -b bin size; or switch to Skipper |
| omniCLIP segmentation fault | Replicate BAMs differ in chromosome order | Re-sort all BAMs with identical reference dictionary |
| CTK CITS finds nothing on PAR-CLIP | Used CITS (truncation) for substitution data | Use CIMS -substitution T C for PAR-CLIP |
| Multi-mapper rescue returns 0 extra peaks | STAR was run unique-only; no multi-mapper BAM | Re-align with --outFilterMultimapNmax 100 --outSAMmultNmax -1 |
| ENCODE stringent peak count = 0 | Forgot SMInput normalization step | Run Yeo lab overlap_peakfi_with_bam_PE.py first; thresholds apply to normalized peaks |
| Strand information lost | samtools view -F 16 filter applied to merged BAM | Strand is encoded in BAM flags; do not pre-split |
| IDR returns no reproducible peaks | Wrong ranking column | Sort by signalValue / log2FC, not score; for narrowPeak format use --rank p.value |
References
- Van Nostrand EL et al 2016 Nat Methods 13:508 (eCLIP, SMInput, ENCODE pipeline)
- Lovci MT et al 2013 Nat Struct Mol Biol 20:1434 (CLIPper algorithm)
- Krakau S et al 2017 Genome Biol 18:240 (PureCLIP HMM)
- Boyle EA et al 2023 Cell Genomics 3:100317 (Skipper, GC-stratified beta-binomial)
- Uren PJ et al 2012 Bioinformatics 28:3013 (Piranha, ZTNB)
- Drewe-Boss P et al 2018 Genome Biol 19:183 (omniCLIP)
- Shah A et al 2017 Bioinformatics 33:566 (CTK / CIMS / CITS)
- Zhang Z & Xing Y 2017 Nucleic Acids Res 45:9260 (CLAM multi-mapper)
- Frith MC et al 2008 Genome Res 18:1-12 (paraclu)
- Li Q et al 2011 Ann Appl Stat 5:1752 (IDR framework)
- Van Nostrand EL et al 2020 Nature 583:711 (A large-scale binding and functional map of human RNA-binding proteins)
- ENCODE eCLIP Standards (encodeproject.org/eclip) - canonical thresholds
Related Skills
- clip-seq/clip-preprocessing - Upstream preprocessing producing dedup BAM
- clip-seq/clip-alignment - Upstream alignment with crosslink-preserving parameters
- clip-seq/clip-qc - FRiP, library complexity, IDR before/after peak calling
- clip-seq/crosslink-site-detection - PureCLIP / CTK CITS / PARalyzer for single-nt CL sites
- clip-seq/differential-clip - DEWSeq / Flipper for cross-condition differential binding
- clip-seq/binding-site-annotation - Annotate called peaks to 5' UTR / CDS / 3' UTR / intron
- clip-seq/clip-motif-analysis - Motif discovery on called peaks
- clip-seq/ago-clip-mirna-targets - Chimeric eCLIP peak calling
- clip-seq/m6a-clip - miCLIP2-specific peak calling
- chip-seq/peak-calling - DNA-protein peak calling for comparison
