Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
Detect single-nucleotide crosslink (CL) sites in CLIP-seq data using truncation patterns (iCLIP/eCLIP CITS), crosslink-induced mutations (HITS-CLIP CIMS deletions, PAR-CLIP T-to-C), or HMM/kernel-density methods (PureCLIP, PARalyzer, CTK). Use when single-nucleotide resolution is required for motif registration (mCross), allele-specific binding (BEAPR), variant-effect prediction, or comparing crosslink chemistry across CLIP variants.
Before using code patterns, verify installed versions match. If versions differ:
CLI: <tool> --version then <tool> --help to confirm flags
Python: pip show <package> then help(module.function) to check signatures
R: packageVersion('<pkg>') then ?function_name to verify parameters
If code throws unexpected errors, introspect the installed tool and adapt the example to match the actual CLI rather than retrying.
CLIP-seq Crosslink-Site Detection
"Detect single-nucleotide crosslink sites in my CLIP data" -> Identify the exact base where the protein-RNA UV adduct caused the reverse transcriptase to stop (truncation, in iCLIP/eCLIP), to read through with a mutation (deletion in HITS-CLIP, T->C in PAR-CLIP), or to leave a multi-base signature (PARalyzer kernel density for PAR-CLIP). Single-nucleotide resolution is the foundation of motif registration (mCross), allele-specific binding (BEAPR/ASPRIN), variant-effect prediction, and the most rigorous comparisons across CLIP variants. The detection chemistry differs by CLIP type: iCLIP/eCLIP read 5' end is one nucleotide downstream of the crosslink (CITS); PAR-CLIP reads contain T->C transitions at the crosslink (CIMS substitution); HITS-CLIP reads contain deletions at the crosslink (CIMS deletion).
CLI (CTK CITS truncations, iCLIP/eCLIP): parseAlignment.pl --map-qual 1 --min-len 18 --mutation-file mut.txt dedup.bam dedup.bed then tag2cluster.pl ... -cs5 5 -m 1 for truncation-cluster
CLI (CTK CIMS deletions, HITS-CLIP): getMutationType.pl dedup.bed mut.txt -type del then CIMS.pl dedup.bed mut.txt -big -c -p 0.01 cims.bed
CLI (CTK CIMS T->C, PAR-CLIP): getMutationType.pl dedup.bed mut.txt -type sub -nuc t -mut c then CIMS.pl dedup.bed t2c.mut -p 0.001 t2c_cims.bed
CLI (PAR-CLIP kernel density): PARalyzer params.ini (parameters file defines read length, min reads per cluster, mutation rate threshold)
CLI (PAR-CLIP wavClusteR R): wavClusteR::filterClusters(cl, snps=NULL, filterFC=FALSE) after wavelet clustering
Single-nt CL sites are the input to mCross motif registration (see clip-seq/clip-motif-analysis), to BEAPR/ASPRIN allele-specific binding analyses, and to RBPNet/DeepRiPe deep-learning models (see clip-seq/clip-deep-learning). They are NOT a replacement for broad peak calls; the two outputs are complementary. A common downstream error is passing a CLIPper peak BED to mCross instead of a PureCLIP single-nt BED - mCross requires the single-nt resolution to register motif position relative to the crosslink offset.
Crosslink Chemistry by CLIP Variant
The detection method must match the underlying chemistry of how the reverse transcriptase encountered the protein-RNA adduct:
CLIP variant
RT behavior at CL
Detection signature
Sensitivity (CL captured per read)
Sequence bias
iCLIP / iCLIP2 / iCLIP3 / eCLIP / irCLIP / FLASH
Truncates at adduct
5' end of cDNA = CL site - 1
~80% of reads truncate; the minority read through
Strong U bias at CL sites
HITS-CLIP
Reads through with deletion (~8-20% of tags)
Single-base deletion in read
~8-20% of tags contain a deletion at the CL site
U bias plus sequence-specific deletion rate
PAR-CLIP (4SU)
Reads through with T->C (20-50% of T positions in crosslinked reads)
T->C transition (or G->A on reverse strand)
Per-T rate 20-50%; per-read 1-5 conversions
Restricted to T positions; depends on 4SU incorporation rate
PAR-CLIP (6SG)
Reads through with G->A
G->A transition
Lower rate than 4SU T->C
Restricted to G positions
miCLIP / miCLIP2 (m6A)
Primarily truncation at the m6A site (RT stops at antibody-trapped m6A); secondary C->T transition observed in a subset of reads at m6A
5' end (CL -1); C->T rate is a feature used by m6Aboost ML in addition to truncation, not a stand-alone primary signal
Mixed; m6Aboost ML integrates truncation + sequence context to score
DRACH motif context required
STAMP
C->T editing on target (not crosslink)
C->T editing in mRNA reads
NA (editing-based; not crosslink-based)
N/A
TRIBE
A->I editing on target
A->G in cDNA (I read as G)
NA
Adjacent to ADAR consensus
Algorithmic Taxonomy
Tool
CLIP variant
Detection signal
Statistical model
Output resolution
Strength
Fails when
PureCLIP (Krakau 2017)
iCLIP/eCLIP/PAR-CLIP
Truncation + enrichment + CL motif
Non-homogeneous HMM
Single-nucleotide
The most comprehensive HMM model
Lowest F1 among callers benchmarked in Boyle 2023 on broad-binding RBPs (highly focal)
CTK CITS (Shah 2017)
iCLIP/eCLIP
Truncation only
Empirical FDR vs background
Single-nucleotide
Simple, well-validated for iCLIP
Less granular than PureCLIP; no HMM smoothing
CTK CIMS deletion (Shah 2017)
HITS-CLIP
Single-base deletions
Empirical FDR
Single-nucleotide
Standard for HITS-CLIP
Requires deletion-tolerant aligner (BWA -e)
CTK CIMS T->C (Shah 2017)
PAR-CLIP
T->C substitutions
Empirical FDR
Single-nucleotide
Alternative to PARalyzer
Less popular than PARalyzer
PARalyzer (Corcoran 2011)
PAR-CLIP
T->C transitions, kernel density
Kernel density estimation
Cluster (10-50 nt)
Field standard for PAR-CLIP
Cluster-level, not single-nt; needs careful parameter tuning
wavClusteR (Comoglio 2015)
PAR-CLIP
T->C with wavelet smoothing
Wavelet transform + clustering
Cluster
Robust to sequencing depth variability
Less single-nt; legacy R package
pyCRAC / kPLogo
CRAC (yeast)
Read truncation + deletion
Empirical
Single-nucleotide
Original CLIP analytics tool
Yeast-focused; perl/python legacy
Piranha bins
Any
Coverage in bins
ZTNB
Bin-level (50-200 nt)
Not crosslink-specific
Bin width too coarse for single-nt
HOMER tag2pos
Any
5' end position
None
Read-end positions only
Quick truncation site dump
No statistical filtering
omniCLIP
Any
Coverage + variant pattern
Dirichlet-multinomial HMM
Region
Not focal
Too broad for single-nt
iCount (paths)
iCLIP
Crosslink site cluster
Empirical
Cluster
Used in nf-core/clipseq
Less single-nt than PureCLIP
Methodology evolves; PureCLIP 2.0 and CTK 1.2 have minor flag changes; PARalyzer parameters need careful tuning per-RBP. Cross-validate single-nt sites with at least two tools when high-confidence reporting is required.
Critical Choice: Truncation vs Mutation vs HMM
Three orthogonal approaches:
Truncation-based (CITS, PureCLIP) -- Find positions enriched in cDNA 5' ends. The RT enzyme stops at the adduct; the 5' end of the read maps to CL site - 1. Used for iCLIP/eCLIP. Pro: high yield (~80% of reads truncate). Con: U bias of crosslinking inflates U positions.
Mutation-based (CIMS for deletions/substitutions; PARalyzer for T->C) -- Find positions with crosslink-induced mutations. RT reads through the adduct with high mutation rate at the CL position. Used for HITS-CLIP (deletions, ~8-20%) and PAR-CLIP (T->C, 20-50%). Pro: less U bias; PAR-CLIP signal is restricted to T positions. Con: lower yield (only mutated reads count).
HMM-based (PureCLIP, omniCLIP) -- Joint model of enrichment + CL signature + sequence context. State the most-likely posterior probability of CL state per nucleotide. Used across CLIP variants. Pro: integrates multiple signals; explicit input normalization. Con: F1 ~0.2 on bulk RBPs (very focal); single-nt resolution at the cost of breadth.
Goal
Method
Tool
Single-nt CL map for motif registration (mCross)
HMM
PureCLIP
Truncation-based ENCODE-compatible iCLIP
Truncation
CTK CITS
PAR-CLIP T->C signal
Mutation
PARalyzer (cluster) or CTK CIMS sub T->C (single-nt)
HITS-CLIP deletion signal
Mutation
CTK CIMS deletion
Cross-CLIP-variant comparable single-nt
HMM
PureCLIP (all variants)
Allele-specific CLIP (BEAPR)
Truncation + ASB
PureCLIP CL sites + WASP-filtered BAM
Variant effect (computational from CL)
HMM
PureCLIP + downstream DeepRiPe (see clip-deep-learning)
Yeast / CRAC
Truncation + deletion
pyCRAC
Per-Tool Failure Modes
PureCLIP -- HMM convergence on sparse coverage
Trigger: RBP with low IP enrichment; SMInput depth uneven; PureCLIP run on full genome without -iv interval.
Mechanism: PureCLIP HMM convergence is sensitive to coverage depth. On regions with < 5 reads/100 bp the HMM defaults to background state; if half the genome is sparse, the state distributions become bimodal and the entire run takes > 24 h or runs out of memory.
Symptom: PureCLIP "Convergence not reached" warning; or output has 0 CL sites; or runtime > 24 h on standard server.
Fix: Restrict analysis to expressed transcripts: -iv expressed_tx.bed. Or filter the BAM to high-coverage regions first. Test on chr22 first to verify parameters before genome-wide run.
PureCLIP -- Misses broad binding zones
Trigger: RBP with broad binding (PUM2 3' UTRs, SR proteins exonic enhancers); using PureCLIP exclusively.
Mechanism: PureCLIP HMM emits the CL state at very high stringency. The Boyle 2023 Skipper benchmark reports PureCLIP as the most focal caller with low recall on broad-binding RBPs.
Symptom: PureCLIP CL site count is 100x lower than CLIPper / Skipper peak count.
Fix: Use PureCLIP for single-nt CL maps AND CLIPper/Skipper for broad-zone peak calls. They are complementary, not substitutes. PureCLIP -or regions output is broader than -o sites but still focal.
CITS truncation -- Misapplied to PAR-CLIP
Trigger: CTK CITS run on PAR-CLIP data.
Mechanism: PAR-CLIP RT reads through the adduct (T->C mutation), not truncates. The 5' end of PAR-CLIP reads is at the fragment 5' end, not the CL site.
Symptom: CITS returns few sites; the sites that ARE returned do not align with the T->C mutation positions.
Fix: For PAR-CLIP use PARalyzer or CTK CIMS substitution mode (-type sub -nuc t -mut c). CITS is iCLIP/eCLIP only.
CIMS deletion -- Misapplied to iCLIP
Trigger: CTK CIMS run with -type del on iCLIP data.
Mechanism: iCLIP RT truncates, doesn't delete. The deletion rate is < 1% in iCLIP (background level), so CIMS finds nothing significant.
Symptom: CIMS output BED has < 100 sites genome-wide.
Fix: Use CTK CITS for iCLIP (truncation-based) or PureCLIP. CIMS deletion is HITS-CLIP / older PAR-CLIP only.
PARalyzer -- Parameter sensitivity
Trigger: PARalyzer default parameters on a new RBP; cluster count unexpected.
Mechanism: PARalyzer's kernel-density approach has 5+ parameters: minimum read depth, minimum mutation read count, mutation rate threshold, bandwidth, kernel type. Different combinations produce 5-100x different cluster counts.
Symptom: PARalyzer cluster count 5-100x off from literature reports for the same RBP.
Fix: Use the PARalyzer default parameters (Corcoran 2011), tuned for that RBP class. Validate on a known-binding region with a reference dataset before publication.
Aligner deletion-tolerance for HITS-CLIP
Trigger: HITS-CLIP aligned with STAR or bowtie2 in standard mode; CIMS finds few deletion sites.
Mechanism: Standard STAR/bowtie2 are aggressive about handling deletions; CIMS expects the deletions to be visible as CIGAR D operations in BAM. STAR/bowtie2 may soft-clip or fail to align deletion-bearing reads.
Symptom: Few CIGAR D operations in BAM (samtools view dedup.bam | awk '$6 ~ /D/' | wc -l); CIMS deletion site count low.
Fix: Re-align HITS-CLIP with BWA-aln (Zhang lab / CTK convention) or STAR --scoreDelOpen -1 --scoreDelBase -1 --scoreInsOpen -1 --scoreInsBase -1 to permit deletions. Or use Novoalign which is more deletion-tolerant.
PAR-CLIP T->C mismatch ceiling
Trigger: PAR-CLIP aligned with STAR --outFilterMismatchNoverReadLmax 0.04; T->C reads discarded.
Mechanism: PAR-CLIP per-T conversion rate 20-50% means a 30 nt read with 8 Ts may have 4 T->C events = 13% mismatch rate, exceeding the 4% ceiling.
Symptom: 40-70% read loss at alignment for PAR-CLIP; downstream T->C site detection finds nothing.
Fix: Raise to 0.07 for PAR-CLIP only (see clip-seq/clip-alignment).
Strand mis-assignment for truncation site
Trigger: Single-end CLIP; using read 5' end as CL site without strand consideration.
Mechanism: For plus-strand RNA, the cDNA 5' end is downstream of the CL position. For minus-strand RNA, it is upstream. Without strand-aware coordinate conversion, half of CL sites are mis-positioned by ~1 nt.
Symptom: mCross / motif analysis shows the motif positioned 1 nt off from expected.
Fix: Verify the BED output handles strand correctly. CTK CITS, PureCLIP, and most modern tools do this automatically; custom scripts must add if strand == '-': cl_position = read_end_5p + 1.
Decision Tree by Use Case
Scenario
Tool
Parameters
Single-nt CL map for mCross motif registration
PureCLIP
-i dedup.bam -ibam sminput.bam -dm 8
iCLIP/eCLIP CITS truncation sites
CTK CITS
tag2cluster.pl -cs5 5 -m 1
HITS-CLIP deletion CIMS
CTK CIMS
CIMS.pl -big -c -p 0.01
PAR-CLIP T->C clusters
PARalyzer
Per-RBP params tuned from Corcoran 2011 defaults
PAR-CLIP T->C single-nt
CTK CIMS substitution
CIMS.pl -type sub -nuc t -mut c -p 0.001
Yeast CRAC
pyCRAC
pyCRAC.py with HTP-tagged protein
Variant effect at CL sites
PureCLIP + DeepRiPe
See clip-seq/clip-deep-learning
Allele-specific binding
WASP-filtered BAM + PureCLIP
See clip-seq/clip-alignment for WASP
Cross-CLIP comparison
PureCLIP (consistent across variants)
Same parameters
m6A miCLIP2 sites
miCLIP2-specific (m6Aboost)
See clip-seq/m6a-clip
STAMP edit sites
Not crosslink-based
See clip-seq/stamp-antibody-free
Reconciliation: When Detection Methods Disagree
Pattern
Likely cause
Action
PureCLIP << CTK CITS site count
PureCLIP HMM very focal; CITS empirical broader
Both correct; report which threshold
PARalyzer clusters << CIMS T->C sites for PAR-CLIP
PARalyzer is cluster-level; CIMS is single-nt
Aggregate CIMS to clusters for comparison
PureCLIP CL sites at unexpected positions
Strand mis-assignment OR aligner soft-clip
Check BED strand column; verify --alignEndsType EndToEnd
HITS-CLIP CIMS empty
Aligner not deletion-tolerant
Re-align with BWA-aln or STAR with adjusted scoring
PAR-CLIP CIMS << expected
Reads lost at mismatch ceiling
Raise STAR --outFilterMismatchNoverReadLmax to 0.07
eCLIP CITS positions shifted by 1 nt
Strand handling off-by-one
Verify R2 5' end position handling
Multiple CITS sites within 5 nt
RT stops near each other; same CL event
Cluster within 10 nt window post-detection
Motif registers 5 nt off in mCross
CL positions wrong by RT-stop offset
Confirm tool reports "CL - 1" position consistently
Operational rule: For motif registration and ASB, run PureCLIP with SMInput. For ENCODE-comparable truncation-based output, also run CTK CITS. Cross-validate by checking that mCross motif PWM is the same when fed PureCLIP sites vs CTK CITS sites. If they diverge by > 2 nt in motif position, suspect strand or off-by-one issue.
Workflow: PureCLIP -> mCross -> ASB
# Step 1: PureCLIP single-nt sites
pureclip \
-i sample.dedup.bam -bai sample.dedup.bam.bai \
-g genome.fa \
-ibam sminput.dedup.bam -ibai sminput.dedup.bam.bai \
-o sample.crosslinks.bed \
-or sample.regions.bed \
-nt 8 -dm 8 -iv expressed_tx.bed
# Step 2: mCross motif registration
mCross -i sample.crosslinks.bed -g genome.fa -k 7 -n 5 -o mcross_out
# Step 3: Intersect with heterozygous SNPs for allele-specific binding
bedtools intersect -wa -wb -s -a sample.crosslinks.bed -b het_snps.vcf > cl_at_hets.bed
# Step 4: Test allele bias with BEAPR or ASPRIN# (see allele-specific CLIP literature; not in this skill)
Common Errors
Error / symptom
Cause
Solution
PureCLIP "Convergence not reached"
HMM didn't converge on sparse coverage
Restrict to expressed transcripts with -iv expressed.bed
PureCLIP > 24h runtime
Full genome on large library
Test on chr22 first; add -iv filter
CTK CIMS empty for HITS-CLIP
Aligner not deletion-tolerant
Re-align with BWA-aln
CITS truncation sites not single-nt
CIGAR S operations from soft-clip
Verify --alignEndsType EndToEnd upstream
PAR-CLIP CIMS empty
Reads lost at mismatch ceiling
Raise STAR mismatch tolerance
Off-by-one motif position
Strand handling differs
Verify tool documents whether output is CL or CL-1
Single-nt motif lost in HOMER on PureCLIP sites
Site BED too narrow; need flanking
Extend bedtools slop -b 15 before motif analysis
mCross "no crosslinks found"
Passed peak BED instead of CL BED
Use single-nt site output
PureCLIP output looks like uniform distribution
R2 5' end trimmed in preprocessing
Re-preprocess; -g and --trim_front2 banned for CLIP
