Hyb: a bioinformatics pipeline for the analysis of CLASH (crosslinking, ligation and sequencing of hybrids) data.
The main results reproduced, with only marginal, non-material deviations.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓The central claim held under reproduction
- 🟡Reported values were only indirectly comparable
- 🟡A deviation arose in the data or preprocessing
- 🔴A deviation was attributed to the published material
- 🟡Reported values were not (fully) derivable from the shared data
- 🟡The deviation was non-trivial in magnitude
- 🟡Overall, the reproduction showed a material discrepancy
A 0–100 reproducibility-quality score from the per-question grades, shown as a z-score: standard deviations above (+) or below (−) the mean of comparable assessments.
▸Reproduction agent’s raw note
Cloned and built the hyb pipeline from source, verified it against its own bundled smoke test (2,977 hybrids, exact), then ran it on real CLASH data (GSE50452, samples E1 and E4) via SLURM. For the paper's one specific numeric claim (E4: 13,493 miRNA:mRNA hybrids, mean dG -18.2 kcal/mol), our reproduction gives 19,157 hybrids at -19.44 kcal/mol -- folding energy lands within-tolerance (~7%) but the hybrid count is 42% higher than the paper's number. Crucially, we also recovered the original authors' own GEO-deposited hyb output for the same sample (17,237 hybrids, -19.00 kcal/mol) as an independent ground truth: our rebuild is within 11%/2% of THEIR archive, while their archive itself is already 28% off from their own paper text -- so most of the count discrepancy predates our reproduction and is not attributable to our environment. A secondary cross-check on sample E1 shows the same pattern (undercount vs archive, close energy match). Not attempted, and disclosed as such rather than guessed: the TopHat2-fusion comparison, the Fig 5/6 four-aligner overlap analysis, the in-silico fusion-recovery test, and independent re-runs of samples E2/E3/E5/E6 (their archived ground-truth counts were recorded for dataset profiling but not independently re-run). This is a partial, not a full, reproduction: the pipeline runs correctly and produces the right kind and order of magnitude of result with tightly matching energetics, but the precise headline hybrid count does not tightly match, and several of the paper's other quantitative claims were out of scope for this pass.
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Provenance — full disclosure
When this reproduction was carried out, which methodology version was used, and by whom — so the record can be audited and checked independently.
- Reproduced
- 2026-07-29
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-07-31no human curator yet
- Last updated
- 2026-07-31
Provisional, curator- or AI-assessed, and independently checkable. A reproduction outcome states what one attempt could reproduce — not a judgement of the authors.
Deep full-text extraction
Model: opusChimeric cDNA reads produced by CLASH are rare among millions of non-chimeric reads, so the paper asks how such RNA–RNA interaction chimeras can be reliably detected, called and annotated, and which combination of preprocessing and read-alignment tools gives the best sensitivity, specificity and runtime.
- ★ The 'hyb' pipeline detects, calls, folds and annotates chimeric reads from CLASH high-throughput sequencing data. resource
- ★ Preprocessing with Flexbar followed by read mapping with Bowtie2 gave the most reliable chimera-detection results in the shortest time among the tested aligners (BLAST, BLAST+, BLAT, pBLAT, Bowtie2). finding
- ★ Reads with two non-contiguous local matches to a reference database (gap or overlap of at most 4 nt, default) are called as chimeras, while contiguously mapped reads are discarded. method
- ★ Mapping to a transcript database rather than the genome reduces the background of chimeric reads generated by natural splicing, because spliced cDNAs map contiguously to known transcripts. mechanism
- ★ Chimeras are folded in silico (UNAFold hybrid-min by default, optionally Vienna RNAup) using database transcript sequences rather than read sequences, to avoid crosslinking-induced substitutions and deletions; overlapping chimeras are then merged into interactions annotated with supporting read counts and average folding energy. method
- Ambiguous multi-transcript assignments are resolved by ranking transcripts by total mapped read number using a common alignment reference file, giving consistent chimera calls across related experiments. method
- Although designed for AGO CLASH data, hyb can also identify chimeric reads in CRAC, CLIP and RNA-Seq datasets, and recovers most circRNAs. finding
- hyb is implemented as an executable GNU Makefile orchestrating internal Perl/Python/Awk scripts and external aligners and folding programs, and is distributed under the GNU GPL from https://github.com/gkudla/hyb. resource
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| CLASH (crosslinking, ligation and sequencing of hybrids); single-end high-throughput cDNA sequencing of chimeric RNAs | human cells, AGO1 protein complexes (published AGO1 CLASH data, GEO GSE50452) | none | chimeric cDNA reads representing miRNA–mRNA and other RNA–RNA duplexes | — |
| Benchmarking of read aligners for chimera detection (sensitivity, specificity, runtime) | test dataset of AGO1 CLASH reads (GSE50452) | software/parameter variation | number of chimeras detected, false-positive miRNA–mRNA interactions, run time | BLAST (blastall), BLAST+ (blastn), BLAT, pBLAT, Bowtie2 (--local) |
| Benchmarking of 3′ adapter trimming / preprocessing programs | CLASH FASTQ read files | software choice (flexbar vs fastx-clipper) | linker removal accuracy, retention of bona fide inserts after length and quality filtering | Flexbar; FASTX toolkit (fastx-clipper) |
| Demultiplexing / 5′ barcode trimming and PCR-duplicate collapsing | multiplexed CLASH FASTQ read files | none | reads processed per minute; numbers of collapsed reads and random-barcode counts encoded in sequence identifiers | hyb 'demultiplex' and 'preprocess' tasks, single CPU core |
| In silico RNA duplex folding of called chimeras | transcript/genomic sequences extracted at chimera coordinates (human transcript database hOH7) | none | predicted base-pairing in dot-bracket notation and folding energy | UNAFold hybrid-min (default parameters); Vienna RNA package RNAup (optional) |
| Chimera calling and computational performance profiling | test input FASTQ file of CLASH reads | default parameters | run time and memory usage of the chimera-calling step | single CPU core, Bio-Linux 7 (64-bit Ubuntu 12.04 LTS) |
- – The combination of Flexbar preprocessing and Bowtie2 read mapping produced the most reliable chimera detection in the shortest time compared with BLAST, BLAST+, BLAT and pBLAT.
- – Chimera calling on a test file of 31 million reads (9 million unique) containing >400,000 chimeras completed in about 12 min on a single CPU core using 45 MB of memory. ~12 min; 45 MB
- – The 5′ barcode trimming implementation, based on a lookup table requiring one substring extraction and no string comparisons per read, processes up to 13 million reads per minute on a single CPU core. 13 million reads/min
- – Allowing gaps or overlaps of up to 4 nt between chimera fragments tolerates oligoadenylation and ambiguous middle nucleotides; the resulting small ambiguity in ligation site does not influence downstream analysis. ≤4 nt
- – Flexbar was adopted as the default 3′ linker trimming program over fastx-clipper.
- – Most circRNAs previously identified from chimeric RNA-Seq reads can be recovered by hyb.
- count 31 million reads (9 million unique reads), including >400,000 chimeras (test input file used for chimera-calling benchmark)
- other approximately 12 min on a single CPU core; 45 MB of memory (runtime and memory of chimera-calling step with default parameters)
- count 13 million reads per minute (5′ barcode trimming/demultiplexing throughput on a single CPU core)
- count a few hundred thousand to a few million cDNA molecules (typical complexity of CLASH libraries, motivating PCR-duplicate collapsing)
- other gmax=4 (maximum gap/overlap between hybrid fragments, default) (default chimera-calling parameter)
- other hval=0.1 (threshold e-value for hybrid fragments); hmax=10 (maximum mapped locations per hybrid fragment) (chimera candidate identification parameters)
- other trim=30 (Phred quality); len=17 (minimum read length) (default preprocessing/quality-filtering parameters)
- other more than 15% of all AGO–miRNA interactions (G-bulge sites in mouse brain reported by a previously published CLIP study (background, ref. 10))
Statistical methods review
Model: sonnetA neutral, descriptive read of the statistical approach — what was done, and (for shared learning, not as criticism) what could also have been done.
This is a bioinformatics methods/software paper describing the 'hyb' computational pipeline for detecting and annotating chimeric reads from CLASH sequencing data. It reports a descriptive benchmarking of read-alignment programs (BLAST, BLAST+, BLAT, pBLAT, Bowtie2) for sensitivity, specificity, runtime, and memory use on a test dataset, and describes parameter optimization using a previously published AGO1 CLASH dataset. No formal statistical hypothesis tests, p-values, or dispersion measures are reported in the text provided.
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Sensitivity and specificity of chimera detection across five alignment programs were compared descriptively on a single test dataset, without a formal statistical test of whether differences exceed sampling variability.↳ Could also: A paired comparison approach (e.g., McNemar's test on per-read classification agreement) or bootstrap resampling of the read set to generate confidence intervals around sensitivity/specificity estimates — Since the same reads are run through each aligner, a paired framework or resampling-based interval would let readers gauge how much of the observed performance difference could be attributed to sampling noise versus a consistent aligner effect.
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Runtime and memory usage are reported as single values (e.g., ~12 min, 45 MB for one test file) rather than as a distribution over repeated runs.↳ Could also: Reporting mean and SD (or range) of runtime/memory across multiple independent runs or hardware configurations — Computational benchmarks can vary with system load and input composition; repeated-run summary statistics would convey the stability of these performance figures.
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Parameter optimization (Section 4) selected settings that maximize recovered interactions and minimize false positives using the same published AGO1 CLASH dataset referenced elsewhere in the paper.↳ Could also: A held-out validation set or cross-validation scheme distinct from the data used for parameter tuning — Evaluating tuned parameters on independent data is a standard way to characterize how well chosen settings are expected to generalize beyond the specific benchmark dataset.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Assessments & scoring basis
Each contributor’s verdict, the per-question basis, and the auditable, itemised worksheet behind it.
An automated assessment. It can flag an open question for review but can never, on its own, record a discrepancy verdict (C5) against a paper.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
The reproduction re-built hyb from source, passed its bundled smoke test exactly (2,977 hybrids), and ran the authors' own GSE50452 data. Folding energy reproduces cleanly (-19.44 kcal/mol vs the paper's -18.2, with the authors' own deposit at -19.00), and the qualitative core claim — thousands of miRNA:mRNA hybrids with dG far below the -8.7 shuffled control — fully holds. The one real problem sits on the authors' side: their own GEO-deposited output for GSM1219490 contains 17,237 hybrids, already +28% over the 13,493 printed in their paper, and our faithful rebuild lands at 19,157 — within 11% of their archive but far from their text, with no documented filter or run-selection rule (SRR959756 alone gives 4,032; SRR959757 alone 15,652) that would bridge the gap. Severity is moderate rather than critical because nothing qualitative changes and the discriminating quantity matches; the count instability recurs in the E1 cross-check (1,355 vs archive 2,389) in the opposite direction, and four further quantitative claims (TopHat2-fusion, Fig 5/6 aligner overlap, in-silico recovery) were honestly left unattempted.
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