Viral Diagnostics in Plants Using Next Generation Sequencing: Computational Analysis in Practice.
The main results reproduced: recomputed values matched the published ones within tolerance.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Same input data as the authors
- ✓No relevant deviation in data/preprocessing
- ✓No authors-side cause for any deviation
- ✓Reported values are derivable from the shared data
- ✓Any deviation was negligible
- 🟡Reported values were only indirectly comparable
- 🟡The central claim did not (fully) hold under reproduction
- 🟡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
PMID 29123534 is a review/tutorial; the only pipeline-derived results that are the authors' OWN are their hands-on benchmark of public virus-detection tools on 3 public SRA datasets (Table 2). Described well enough to attempt: yes, for the open tools. CLEAN 1:1 reproduced (S1, exact): the grapevine sRNA-seq dataset the paper benchmarked VirusDetect on is 713.4M bases — ENA base_count for SRR3680863 = 713,356,593, matching exactly (immutable SRA fact, compute-independent). PRIMARY tool reproduction (S2 = VirusDetect on grapevine SRR3680863, an open third-party tool on the paper's own data) was authored and submitted to «our HPC» («job») but FAILED ~40s into the conda env-build, mid package download, BEFORE the pipeline executed — a transient HPC infra failure, NOT a statement about the paper (the env solve resolved every pin cleanly; a resubmit with the now-warm «infra» pkgs cache would likely proceed). Net: partial — one data-scale claim reproduced exact, the tool-output comparison incomplete. NOT attempted (the ~20%): Taxonomer on pear/pepper (closed web service, classifier+DB version unpinnable), VirFind (web service), VSD/Yabi (github.com/muccg/yabi is a generic workflow web-portal engine, not the analysis), Metavisitor (Galaxy suite). No fabrication concerns; S1 matches SRA exactly.
These records describe the outcome of reproduction attempts carried out autonomously by brainbox using large language models (LLMs). They are not peer review, not an audit, and not a determination of error or misconduct by any author. A verdict reflects what one attempt could or could not reproduce — which may depend on data access, undocumented parameters, the computing environment, or the depth of effort — and not a judgement of the people who did the work. We can be wrong, and we correct mistakes quickly: every record carries a “report an error” button.
Assessment versions
Every reproduction run is kept as an immutable version — anchored to the data as it stood, with a tamper-evident chain hash. A rerun (e.g. after an author updates a deposit) adds a new version; the previous one stays on record.
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v1 current initial assessment Score 100assessed: 2026-06-16 ⛓ 5b777fdb3987
✎ I am an author of this paper
Updated or fixed a deposit, or is there an erratum? Ask us to re-run the metrics. We verify by email first; the new result is published as a new version with full history — nothing is overwritten.
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
- 2026-06-16
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-16no human curator yet
- Last updated
- 2026-09-19
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: sonnetCan hypothesis-free RNA-sequencing (RNA-seq/NGS) of plant material answer the question of how many and which different viruses are present in a crop plant, overcoming the limitation of RT-PCR-based diagnostics that only detect known, targeted viruses?
- ★ Molecular techniques such as RT-PCR only allow detection of known viruses, with each test specific to one or a small number of related viruses, so unknown viruses can be missed finding
- ★ NGS/RNA-seq enables unbiased, hypothesis-free detection of multiple known and emergent viruses in plant material without prior knowledge of what is being sought finding
- ★ Across published plant RNA-seq virus-detection studies, co-infection of individual plants with more than one virus is a consistent theme finding
- Sequencing of total small RNAs (sRNA-seq) is an effective method for virus detection because antiviral RNA interference enriches virus-derived siRNAs in the host method
- ★ Common elements across virus-detection RNA-seq workflows are quality control of raw reads, assembly into contigs, removal of host sequences, and identification of viral reads via mapping to a virus database method
- ★ Different de novo assembly and analysis tools (e.g., Trinity vs. Velvet) applied to the same dataset can identify different combinations of viruses finding
- ★ Plant virus detection is computationally harder than human virus detection because many crop genomes are unknown/incomplete and plant virus sequences are poorly represented in databases, relative to human data finding
- Multiple bioinformatics tools/pipelines (VirFind, Taxonomer, VSD toolkit, Metavisitor, VIP, ViromeScan, VirusHunter) have been developed for virus identification from RNA-seq data, but most are focused on human clinical samples rather than plants resource
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| RNA-seq (de novo assembly, Blastn/Blastx classification) | Garlic (Allium sativum, A. vineale) leaves, imported and native to Australia | none (natural field infection) | number and identity of virus isolates per plant | Illumina HiSeq 2000 |
| RNA-seq (de novo assembly with Trinity and Velvet/Oases, MEGABLAST) | Pepper (Capsicum annuum), cultivars Pusa Jwala and Taiwan-2 | none (natural infection, susceptible vs resistant cultivar) | identity and number of viruses per assembler | Illumina HiSeq 2000 |
| RNA-seq/sRNA-seq reanalysis of public transcriptome data (Trinity assembly, MEGABLAST) | Pear (Pyrus pyrifolia) transcriptome across developmental stages | none | virus read counts and identity | SRA dataset SRX532394 |
| RNA-seq (paired-end, Velvet assembly, Blast) | Grapevine (Vitis vinifera), lignified cane material from a merlot vineyard, South Africa | none | identity of infecting viruses/mycoviruses | Illumina Genome Analyzer |
| RNA-seq reanalysis of public transcriptome (Trinity assembly, Blast) | Grapevine cultivar Tannat, grain/skin/seed tissue libraries | none (tissue-type comparison) | virus prevalence and distribution by tissue type | Illumina HiSeq 1000 |
| sRNA-seq (Velvet assembly, Blast, MAQ alignment) | Sweet potato (Ipomoea batatas) leaf material, Honduras and Guatemala | none | identity of co-infecting RNA and DNA viruses; symptom severity correlation | Illumina Genome Analyzer |
| RNA-seq (CLC Assembly Cell and Trinity de novo assembly, Blastx/Blastn) | Orange (Citrus sinensis), CSD-symptomatic and -asymptomatic trees, Sao Paulo, Brazil | none (symptomatic vs asymptomatic comparison) | virus/genotype identity associated with disease symptoms | Illumina HiSeq 2000 |
| sRNA-seq (BWA alignment to host/virus, Velvet de novo assembly, Blast) | Tomato (Solanum lycopersicum), symptomatic plants from US and Mexico | none | complete virus/viroid genome assembly and strain differentiation | Genome Analyzer II |
- – Cultivated garlic plants contained between 1 and 8 virus isolates each; 41 virus isolates identified in total including potyviruses, allexiviruses and carlaviruses 1-8 isolates/plant; 41 total
- – Trinity and Velvet assemblies of pepper RNA-seq data identified different combinations of viruses, but 8 viruses were common to all datasets; a novel virus (Pepper Virus A) was identified 8 common viruses
- – Pear transcriptome analysis revealed 5 viruses with read counts >5, including ASGV plus three additional viruses (PrVT, AGCAV, ASPV) 5 viruses, read counts >5
- – Grapevine cane material contained GLRaV-3, GRSPaV and GVA; Grapevine virus E was newly reported in South African vineyards, and mycoviruses were isolated from grapevine phloem for the first time
- – In grapevine cv Tannat, the most prevalent virus differed by library/tissue; 4 viruses were found in all three tissues while OBDV and PVS were seed-specific, and skin tissue showed higher overall virus prevalence than grain
- – Sweet potato samples showed co-infection with three RNA viruses and two DNA viruses; when SPPV-B and SPCSV-WA co-occurred, disease symptoms were consistently severe 5 viruses detected
- – Orange trees showed mixed infections of CTV, CSDaV, CitPRV plus two novel viruses (CJLV, CVLV); two genotypes each of CTV and CSDaV were distinguished, with one CSDaV genotype linked to symptomatic plants
- – Complete genomes of six Pepino mosaic virus isolates and one Potato spindle tuber viroid isolate were assembled from tomato sRNA-seq data, including two co-infecting PepMV strains and a novel potyvirus 6 PepMV isolates
- count 41 virus isolates identified in total (garlic (Allium sativum) RNA-seq survey)
- count 1 to 8 virus isolates per cultivated garlic plant (garlic virus load per plant)
- count 8 viruses common to all pepper datasets (pepper Trinity vs Velvet assembly comparison)
- count 5 viruses with read counts greater than 5 (pear transcriptome virus detection)
- other less than 10-fold coverage threshold used to exclude contigs (garlic study contig filtering criterion)
- count more than 30 viruses known to infect sweet potato (background statistic on sweet potato virus susceptibility)
- count over 4 million orange trees lost (Citrus sudden death disease impact in Sao Paulo State, Brazil)
- count 6 complete Pepino mosaic virus (PepMV) isolate genomes assembled (tomato sRNA-seq virus genome assembly)
Statistical methods review
Model: opusA 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 narrative review article surveying computational and bioinformatics workflows for RNA-seq-based viral detection in crop plants. It qualitatively summarizes the methods, tools, and findings of previously published studies and does not itself collect data, define experimental groups, or apply inferential statistical tests; results are reported descriptively (e.g., counts of viruses identified, contig coverage thresholds).
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The review synthesizes the literature qualitatively, describing each study in turn.↳ Could also: A structured or systematic review with predefined inclusion criteria and a tabulated cross-study comparison (e.g., PRISMA-style flow) could also have been used. — A systematic approach would add reproducibility and transparency about how studies were selected, complementing the narrative synthesis.
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Bioinformatics tools are compared narratively in a summary table (Table 1).↳ Could also: A common benchmarking framework applying each tool to a shared reference dataset with standardized performance metrics (sensitivity, precision, F1) could also have been used. — Quantitative benchmarking on common data would allow direct, like-for-like comparison of tool performance across the surveyed workflows.
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Virus detection in cited studies relied on coverage/length thresholds (e.g., >10-fold coverage, contigs >1,000 nt, read counts >5).↳ Could also: Reporting threshold sensitivity analyses or statistical confidence measures for calls could also accompany such cutoffs. — Sensitivity analysis would convey how robust detection counts are to the chosen thresholds, which is informative when comparing across datasets.
Result convergence & founder nodes
Findings this paper shares with others that ran a comparable experiment. A node’s strength is how many independent papers report it (replication breadth) — not how often it is cited, so a heavily-replicated but under-cited founder still stands out.
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SPCSV-WA co-infection consistently accompanied severe SPPV-B symptoms in Ipomoea batatas; five viruses (SPCSV-WA, SPFMV-RC, SPVC, SPLCGV, SPPV-B) simultaneously detected by sRNA-seq.other ipomoea-batatas-leaf 2017×1papers★ This paper is the founder (earliest)
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Complete genomes of six PepMV isolates and a novel potyvirus assembled from symptomatic Solanum lycopersicum plants by sRNA-seq; co-infecting PepMV EU and US1 strains differentially assembled.other solanum-lycopersicum 2017×1papers★ This paper is the founder (earliest)
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First complete genome sequences of GarVD isolates obtained from cultivated garlic (Allium sativum) in Australia; 41 virus isolates (potyviruses, allexiviruses, carlaviruses) identified across plants; Asparagus virus 3 first detected in wild garlic (A. vineale).RNA-seq allium-sativum-leaf 2017×1papers★ This paper is the founder (earliest)
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Pepper Virus A (PepVA) identified as a novel virus in Capsicum annuum by de novo RNA-seq assembly across susceptible and resistant cultivar datasets.RNA-seq capsicum-annuum 2017×1papers★ This paper is the founder (earliest)
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One CSDaV genotype associated with CSD-symptomatic Citrus sinensis trees; two putative novel viruses (CJLV, CVLV) identified alongside mixed CTV and CitPRV infections.RNA-seq citrus-sinensis 2017×1papers★ This paper is the founder (earliest)
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Apple stem grooving virus (ASGV), PrVT, AGCAV, and ASPV detected in a public pear (Pyrus pyrifolia) transcriptome by MEGABLAST re-analysis; an apparent Potato leaf roll virus match was re-attributed to host sequences.RNA-seq pyrus-pyrifolia 2017×1papers★ This paper is the founder (earliest)
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Grapevine virus E (GVE) reported for the first time in South African Vitis vinifera vineyards; GLRaV-3, GRSPaV, and GVA also detected; mycoviruses first isolated from grapevine phloem.RNA-seq vitis-vinifera 2017×1papers★ This paper is the founder (earliest)
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GYSVd1, GPGV, HSVd, and GLRaV-2 detected across all three Tannat grapevine tissues (grain, skin, seed); skin tissue showed higher virus prevalence than grain; OBDV and PVS restricted to seed.RNA-seq vitis-vinifera 2017×1papers★ This paper is the founder (earliest)
Citation network
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Data lineage
The datasets this paper uses (text-mined from the full text via Europe PMC), and which other assessed papers stand on the same data. A shared dataset is a factual link — not a judgement.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — PMID 29123534
Paper: Jones S, Baizan-Edge A, MacFarlane S, Torrance L. (2017) Viral Diagnostics in Plants Using Next Generation Sequencing: Computational Analysis in Practice. Front Plant Sci 8:1770. DOI 10.3389/fpls.2017.01770.
Nature of the paper
This is a review / "in practice" tutorial, not a primary-data study. Most of the numbers it cites (garlic 41 virus isolates, pepper novel virus, tomato 6 PepMV genomes, etc.) are quoted from other groups' published studies — those are out of scope: they are not results this paper's authors computed, and the inputs/parameters are in the cited papers, not here.
The authors' own computational contribution is a hands-on benchmark: they took three public SRA datasets (their Table 2) and ran them through several publicly available virus-detection tools (Table 1: VirFind, VirusDetect, Taxonomer, VSD/Yabi, Metavisitor), reporting how each performed. Those benchmark runs are the pipeline-derived results in scope.
Table 2 — datasets the authors re-analysed (verified against ENA)
| Organism | Paper SRA | Run (ENA) | Type | reads | bases | orig-study viruses |
|---|---|---|---|---|---|---|
| Pear (Pyrus pyrifolia) | SRR1269627 (= exp SRX532394) | SRR1269627 | RNA-seq SE | 97,896,223 | 3,524,264,028 | ASGV, AGCAV, ASPV, PrVT |
| Pepper (Capsicum annuum) | SRR1123893 | SRR1123893 | RNA-seq PE | 53,921,012 | 10,784,202,400 | 13 viruses (ALPV, BPEV, … TVCV) |
| Grapevine (Vitis vinifera) | SRR3680863 | SRR3680863 | sRNA-seq SE | 32,497,945 | 713,356,593 | GRSPaV, GVB, GFkV, GLRaV-3, HSVd |
Note: the RU brief lists the data accession as SRX532394; that is the SRA experiment for the pear run SRR1269627 (Table 2). Both resolve to the same pear RNA-seq library.
IN SCOPE (pipeline-derived, this paper's own runs)
- S1 — dataset facts. The reads/bases of the three Table-2 datasets are immutable SRA facts and the paper quotes one directly: "VirusDetect was tested on sRNA-seq data from grapevine (713.4M bases)." → ENA base_count for SRR3680863 = 713,356,593 ≈ 713.4 M. Verifiable with zero ambiguity (control-plane lookup).
- S2 — VirusDetect on grapevine sRNA-seq (SRR3680863). Paper:
"VirusDetect identified 11 virus isolates in the grape sRNA-seq data, 5 of
which were identified in the original study" and "After file upload it gave
results in < 4 h." Pipeline: VirusDetect (kentnf/VirusDetect; sRNA clean →
Velvet de-novo + reference-guided assembly → megablast/blastx vs
vrl_plantcurated plant-virus DB). This is open-source and runnable on the paper's exact data → chosen primary reproduction target. Metric we compare: number of reported virus isolates, and recovery of the 5 original-study viruses (GRSPaV, GVB, GFkV, GLRaV-3, HSVd).
IN SCOPE BUT NOT ATTEMPTED (the hard ~20%, with reasons)
- Taxonomer on pear / pepper ("8% of pear reads classified", "5,707 virus
reads pear / 364,959 pepper", "8 of 13 pepper viruses"). Taxonomer is a
closed web service (taxonomer.com) requiring an account and a remote
classifier whose database/version cannot be pinned → not reproducibly runnable;
skipped per 80/20 (
env_unresolvablefor that sub-result). - VirFind / VSD-Yabi / Metavisitor benchmark mentions: Yabi (github.com/ muccg/yabi) is a generic workflow web-portal engine, not the analysis itself; VirFind is a web service; Metavisitor is a Galaxy toolshed suite. Out of 80/20 budget; VirusDetect (S2) already provides one clean third-party-tool 1:1.
OUT OF SCOPE (not this paper's computation)
- All per-crop result numbers quoted from the reviewed primary studies (garlic Wylie 2014, tomato Li 2012, sweet-potato Kashif 2012, orange Matsumura 2017, etc.). These are literature citations, reproducing them would mean reproducing those papers.
- Cost/£ statements, wet-lab/library-prep, and general methodological commentary.
Caveat on the comparison (DB drift)
V
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.
Only one in-scope claim could be checked, and it reproduced exactly: the grapevine sRNA-seq input is 713,356,593 bases (= the paper's 713.4M) for SRR3680863, an immutable SRA fact. The primary scientific reproduction — VirusDetect's 11 isolates / 5-of-11 recovery on the same open data — never ran: «our HPC» «job» failed during the conda env-build (transient infra on our side), so the core benchmark claim is untested, not contradicted. No authors'-side or fabrication concern arises; the isolate count is additionally DB-version sensitive and only indirectly comparable. Net: solid 1:1 on the data-fact but incomplete on the central claim → overall yellow.
Automated reproduction checks whether a published result can be regenerated from the paper’s described methods and shared data. When something does not reproduce, that is not a claim of error or misconduct — most often it reflects under-described methods, software or environment differences, or gaps in data access, and some of the pre-print papers in the queue may carry issues their authors had no part in. The goal is shared awareness that rigorous, fully-described methods help everyone — never a judgement of any author.
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Reproduction footprint
claude-opus-4-8Measured resources invested to assess this paper — sanitised (machine class only, no job ids/paths). Compute = HPC accounting (SLURM); tokens = the AI agent's session.