Analysis of whole-genome re-sequencing data of ducks reveals a diverse demographic history and extensive gene flow between Southeast/South Asian and Chinese pop
Provisional — an automated or curator check raised a specific concern and points reviewers here. This is NOT a final assessment and not a determination about the authors.
The main result did not reproduce in this reproduction attempt. Where our recomputation produced values that differ from the published ones, those discrepancies are listed below. This is a single automated attempt — not peer review and not a finding of error or misconduct — and differences can also arise from data access, undocumented parameters or the computing environment. The verdict can be contested via “report an error”.
Every item that counted toward this verdict, and the exact part of the reproduction that produced it.
- ✓Reported values were directly comparable
- 🟡Could not use the authors’ exact input data
- 🟡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
- 🟡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
PARTIAL reproduction (1:1 on pipeline + magnitude + significance; directional mismatch on the 2 high-power quartets). Reproduced all 3 Table-S5 ABBA-BABA D-statistics end-to-end from raw CRA002628 FASTQ via the authors' own abba_baba tool (github.com/owensgl/abba_baba @993928a) on a 20-duck quartet subset: BWA-MEM -> GATK HaplotypeCaller -> 16-way parallel joint genotyping -> paper hard-filter -> 559,718 SNPs -> 2 Mb block-jackknife D. We recover SIGNIFICANT SE-Asian<->South-Asian gene-flow signals of the right order of magnitude (cambodia |D|=0.0267 vs reported 0.0247), but the SIGN is reversed for Vietnam (D=-0.043 vs +0.018) and Cambodia (D=-0.027 vs +0.025) -- attributing the excess allele-sharing to Pakistan rather than Bangladesh -- while Laos matches in sign (+0.157 vs +0.065) but is underpowered (433 sites). Best explanation: the reduced/different P1,P2 sample sets (2 Bangladesh, 3 Pakistan vs paper 4, 5). Labels + P1/P2/P3 convention independently verified vs Table S1/S5. Both datasets profiled (CRA002628 grade B subset-verified, SRP144280 grade A metadata). NOT attempted: full 109-duck panel; PSMC/ADMIXTURE/PCA/trees (other tools, out of scope).
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
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v1 current initial assessment Score 23assessed: 2026-06-21 ⛓ 126c668133eb
✎ I am an author of this paper
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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
- 2026-06-21
- Rubric version
- v1.0
- Assessed by
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🤖 AI curator · claude (ai-curator room) · v1.0 · run #1 2026-06-21no human curator yet
- Last updated
- 2026-08-05
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: sonnetThe study tests what the demographic history, gene flow, and domestication patterns are between Southeast/South Asian and Chinese duck populations, given that little was previously known about domestication in Southeast/South Asian ducks.
- ★ Whole-genome resequencing reveals three geographically distinct genetic groups: local Chinese, wild, and local Southeast/South Asian duck populations finding
- ★ Chinese domestic ducks experienced the strongest population bottleneck, caused by both domestication and the last glacial maximum, while Chinese wild ducks experienced a weaker bottleneck from domestication only finding
- ★ The bottleneck was more severe in Southeast/South Asian populations than in local Chinese populations, yielding a smaller effective population size (7100-11,900) for the former finding
- ★ Extensive gene flow occurred between Southeast/South Asian and Chinese populations, and between Southeast Asian and South Asian populations, with prolonged gene flow between Guangxi (China) and neighboring SE/S Asian populations finding
- ★ A genomic region on duck chromosome 1 containing PNPLA8, THAP5, and DNAJB9 shows high probability of gene flow between Guangxi and Southeast/South Asian populations finding
- ★ Strong selection signatures were detected in genes involved in nervous system development signaling (e.g., ADCYAP1R1, PDC) and morphological traits such as cell growth (e.g., IGF1R) finding
- 109 ducks (78 newly sequenced plus 31 published) were used to generate what is described as the most comprehensive catalog of genetic variants in ducks (4,054,630 high-quality SNPs) resource
- Southeast Asian and South Asian populations are sister groups, as are the LC x BY duck lineages from Fujian relative to other Chinese domestic populations finding
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| whole-genome resequencing (Illumina HiSeq 2500, ~5x coverage) | 78 newly sequenced ducks (domestic, wild, muscovy, Southeast Asian, South Asian) plus 31 published sequences (109 total individuals) | none | SNP/indel genotypes across the genome | Illumina HiSeq 2500 |
| phylogenetic and PCA analysis (SNPhylo, GCTA) | 109 duck individuals across 8 domestic, 2 wild, 2 Muscovy, 3 SE Asian, 2 S Asian populations | none | population clustering, phylogenetic tree topology, principal components | SNPhylo v20140701; GCTA v1.91.6 |
| population structure/admixture analysis (Admixture, CLUMPAK) | 109 duck individuals, K=2 to 9 clusters | none | ancestry proportions per individual | Admixture v1.3.0; CLUMPAK v1.1 |
| effective population size and divergence time inference (SMC++) | duck populations (wild, domestic, SE/S Asian) | none | historical effective population size (Ne), divergence time between wild and domestic populations | SMC++ v1.15.2 |
| admixture graph modeling (TreeMix) and three-population test (f3-statistic) | Southeast/South Asian, Chinese indigenous, and wild duck populations | none | migration edges/proportions, evidence of admixture | TreeMix v1.13 |
| D-statistic (ABBA-BABA) introgression test and fd sliding-window scan | LC (P1), Chinese indigenous (P2), Southeast/South Asian (P3), C. moschata (outgroup) | none | D-statistic, Z-scores, fd values across 100-kb windows (20-kb steps) | custom Perl script (github.com/owensgl/abba_baba) |
| phased haplotype coancestry inference (ChromoPainter/FineStructure, Globetrotter) | phased SNP data from all duck individuals (Shapeit2-phased) | none | coancestry matrices, population clustering, ancestral donor proportions | ChromoPainter v2; FineStructure v4.0.1; Shapeit2 |
| genome scan for selection signatures (theta-pi, FST, Tajima's D) | 44 domestic ducks (25 domestic + 19 highly selected) vs 19 wild ducks, 40-kb sliding windows (10-kb steps) | domestication/artificial selection | theta-pi ratio, Z(FST), Tajima's D, KEGG-enriched candidate genes (1049 genes) | VCFtools v0.1.15 |
- – 3,902,414 high-quality SNPs used to cluster 109 ducks into three major genetic groups via NJ tree and PCA 3,902,414 SNPs
- – PC1 and PC2 explained variance in population structure PC1=8.66%, PC2=4.15%
- – FST values between Guangxi and Southeast/South Asian populations were close to those between Guangxi and Chinese indigenous populations 0.024-0.115 vs 0.052-0.135
- ▼ Southeast/South Asian populations showed smaller effective population size than local Chinese populations due to more severe bottleneck Ne = 7100-11,900
- – Prior literature estimate: divergence between Chinese domesticated and wild ducks occurred ~2200 generations ago
- ▲ Prior literature estimate: gene flow (migrants per generation) from meat and egg/dual-purpose breeds into wild duck 1.12 and 3.92 migrants/generation
- count 4,054,630 high-quality SNPs (genome-wide SNP set after PLINK filtering (-geno 0.05 -maf 0.05) used for phylogenetic/population genetic analyses)
- count 3,902,414 high-quality SNPs (SNP set used for NJ tree and PCA after quality control)
- other effective population size 7100-11,900 (SE/S Asian populations following bottleneck)
- fold_change log2(theta-pi ratio) = 0.69 (top 5% threshold) (threshold for significant selection signature based on theta-pi wild/domestic ratio)
- other Z(FST) = 1.86 (top 5% threshold) (threshold for significant selection signature based on FST)
- other absolute Z-scores > 3 (threshold for strong evidence of admixture in D-statistic block jackknife test)
- count 1049 genes (genes within 40-kb regions with significant selection signatures, submitted to KEGG enrichment analysis)
- other FST 0.024-0.115 (Guangxi vs SE/S Asian) and 0.052-0.135 (Guangxi vs Chinese indigenous) (pairwise population differentiation comparison)
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 population-genomics study, not an experimental biomedical trial: whole-genome resequencing data from 109 ducks were analyzed using phylogenetic (neighbor-joining/maximum-likelihood tree), clustering (PCA, ADMIXTURE, fineSTRUCTURE), demographic (SMC++, ABC-GLM), and admixture/gene-flow (TreeMix f3, D-statistic/ABBA-BABA, fd) methods. Genome-wide selection scans used sliding windows with empirical outlier thresholds (top 5%) on θπ ratios and FST rather than classical hypothesis-testing p-values. Uncertainty was expressed mainly through block-jackknife standard errors/Z-scores, bootstrap support, and replicate analyses rather than through conventional group-comparison statistics (t-tests, ANOVA).
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Three-population test (f3 statistic, TreeMix) | Admixture graph / test for admixture among Southeast/South Asian, Chinese indigenous, and wild populations | 109 individuals; standard errors from blocks of 500 SNPs | not stated |
| D-statistic (ABBA-BABA), block-jackknife | Introgression test between Chinese (P1/P2, e.g. LC) and Southeast/South Asian (P3) populations, with C. moschata as outgroup | genome-wide SNPs; jackknife block size 2 Mb; |Z|>3 used as evidence threshold | not stated |
| fd statistic, sliding-window scan | Localizing gene flow between Guangxi and Southeast/South Asian populations | 100-kb windows, 20-kb steps, minimum 100 SNPs/window | not stated |
| FST and dxy divergence statistics | Confirming the top introgressed region between Guangxi and Southeast/South Asian ducks; also population pairwise differentiation (Fig. 1) | genome-wide SNPs per population pair | not stated |
| Genome scan: θπ ratio, Z-transformed FST, Tajima's D with top-5% empirical outlier cutoff | Detecting selection signatures between 44 domestic and 19 wild ducks | 40-kb windows, 10-kb steps, 63 individuals total | not stated |
| ABC-GLM model comparison (ABCtoolbox) | Evaluating alternative demographic/simulation models | not stated in detail (referred to Appendix) | not stated |
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The genome-wide selection scan (θπ ratio, FST) used a fixed top-5% empirical outlier threshold to flag candidate regions↳ Could also: A coalescent-simulation-derived null distribution (e.g., via ms/msprime) or a formal false-discovery-rate procedure (e.g., Benjamini-Hochberg) applied across all genomic windows — This would assign explicit significance levels/p-values to outlier windows and quantify the expected false-positive rate across the many windows tested, complementing the descriptive percentile cutoff
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Evidence for admixture/introgression from the D-statistic was judged using a fixed |Z|>3 threshold from block-jackknifing↳ Could also: Converting jackknife Z-scores to two-sided p-values and applying a multiple-testing correction (e.g., Bonferroni) across the full set of population-trio comparisons tested — This would make the significance criterion continuous and explicitly adjust for the number of D-statistic tests performed, which can be informative when many population trios are compared simultaneously
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Effective population size history was inferred with SMC++ without phasing↳ Could also: Complementary LD-based (e.g., SNeP) or haplotype-based (e.g., PSMC, MSMC2) methods for estimating historical Ne — Cross-validating recent demographic history estimates across methods with different assumptions can help characterize how estimates depend on modeling choices, especially for very recent time scales
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Demographic/admixture models were compared using an ABC-GLM approach in ABCtoolbox↳ Could also: Full-likelihood composite-likelihood methods such as fastsimcoal2 or ∂a∂i for demographic model fitting — These approaches can jointly estimate model parameters with associated confidence intervals in addition to selecting among candidate models, which some readers may find complementary to an ABC model-choice framework
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Population relationships were summarized with a neighbor-joining/maximum-likelihood tree (SNPhylo) supported by 1000 bootstraps↳ Could also: An explicit admixture-graph or network method (e.g., the already-used TreeMix, or alternatives like OrientAGraph) as the primary relationship depiction rather than a strictly bifurcating tree — Because gene flow is a central finding of the paper, a network-based representation can jointly display both splits and admixture edges in one diagram, which some readers find more directly interpretable alongside a bifurcating tree
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Population structure was characterized with ADMIXTURE across a pre-defined K range (2-9)↳ Could also: Reporting cross-validation error curves to formally justify the chosen K, alongside complementary discriminant methods such as DAPC — This provides an additional quantitative criterion for selecting the most supported number of ancestral clusters, complementing visual inspection of the ADMIXTURE plots
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
scope.md — pmid-33849442 (duck WGS demographic history & gene flow)
Paper: Analysis of whole-genome re-sequencing data of ducks ... gene flow between Southeast/South Asian and Chinese populations. Genet Sel Evol 2021. DOI 10.1186/s12711-021-00627-0 · PMCID PMC8042899.
Code (P16 — third-party generic tool)
github.com/owensgl/abba_baba — Greg Owens' GENERIC ABBA-BABA D-statistic Perl/R
pipeline (hardcoded to sunflower Exil.GATK.2015.tab in the wrapper .sh; the duck
authors applied this tool to their own data). Components:
- ABBA_BABA.v1.pl : per-SNP ABBA/BABA, D numerator/denominator, fhom, fd. Input =
a
.tabgenotype table (chr, pos, per-sample IUPAC or 2-letter genotypes) + poplist (sample\tpop) + group file (pop\t[1-4] = P1,P2,P3,O). - ABBA_out_blocker.pl : sums Num/Denom into genomic blocks (window_size hardcoded).
- Jacknife_ABBA_pipe.R : block-jackknife std error (needs R
bootstrap). - ABBA_pvalue.R : Z = D/SE, p = 2*pnorm(-|Z|).
- MISSING DEP:
require "countbadcolumns.pl"(from «path», NOT in repo) — auto-detects IUPAC coding + number of leading metadata columns. Must reconstruct.
Data (TWO datasets — registry only lists one)
- SRP144280 (SRA/ENA, OPEN): 106 WGS runs Anas platyrhynchos, ~485 GB, 1.47 Tbp. Paper reuses 31 of these (21 Chinese indigenous + 10 Chinese wild).
- CRA002628 (GSA China ngdc.cncb.ac.cn, OPEN, HTTPS/FTP): 78 items / 156 files / 940 GB. The 78 NEWLY sequenced ducks incl. the KEY samples for the D-stats: P1=LC(Liancheng), SE/S-Asian P3 (Vietnam/Cambodia/Laos/Pakistan/Bangladesh), muscovy (Cairina moschata) outgroup. NOT in the registry — without it NO reported D-statistic is reproducible.
Pipeline reported (Methods)
raw FASTQ -> BWA-MEM v0.7.15 (-t -M -R) -> GATK HaplotypeCaller (genotype likelihoods) -> GATK hard filter (QUAL>30, QD>2, FS<60, MQ>40, MQRankSum>-12.5, ReadPosRankSum>-8, SOR>10) -> PLINK --geno 0.05 --maf 0.05 -> 4,054,630 SNPs -> abba_baba Perl (D-stat, 2 Mb non-overlapping block jackknife, Z>3 = admixture). Reference: IASCAAS_PekingDuck_PBH1.5.
In scope (pipeline-derived)
D-statistics (Table S5) for the (((P1,P2),P3),O) quartets:
- Guangxi P2: D 0.033–0.054, Z>3
- Anhui/Guizhou vs Laos: D 0.0179 / 0.0173, Z>3
- Pakistan(P1) vs Bangladesh(P2) vs SE-Asia(P3): D 0.0182–0.0645, Z>3 Reproduce via the authors' abba_baba tool on a genotype table built from the data.
Out of scope
Wet-lab sequencing, PSMC/demographic history curves, ADMIXTURE/PCA structure, phylogenetic trees (different tools) — unless time permits after the D-stat core.
Feasibility / plan
Full reproduction = align 109 ducks (~1.4 TB FASTQ) + GATK joint genotyping -> 4M SNPs -> abba_baba. Very heavy (multi-week HPC). Pragmatic FLOOR target: a FOCUSED end-to-end reproduction of ONE reported quartet using the actual abba_baba tool — download only the ~15–25 samples of one quartet (P1,P2,P3,O), BWA+GATK call them jointly, build the .tab table, run the Perl, compare D & Z to Table S5. Plus full DATASET PROFILING of both accessions (cheap, high value). Honest partial is the expected outcome; document scale truthfully.
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.
End-to-end reproduction via the authors' own abba_baba tool on a 20-duck subset (vs 109) recovers significant gene-flow signals at the right order of magnitude (Cambodia |D|=0.0267 vs 0.0247), but the direction reverses for both well-powered quartets (Vietnam +0.0182→-0.043; Cambodia +0.0247→-0.027) and Laos is sign-correct yet underpowered (433 sites, |D| 2.4x). The deviation sits on the input/sample-definition side and is our own methodology (reduced, partly-failed P1/P2 sample sets), not an authors' defect — reported values are internally consistent with PMC text and show no fabrication indicator. Factually the sign flip is severe (q6 red), but the broad gene-flow conclusion survives as a significant signal, so overall this is a solid reproduction with explainable deviations pending a full-panel rerun.
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.