Main Factors Influencing the Gut Microbiota of Datong Yaks in Mixed Group.
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
- ✓Reported values were directly 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
- 🟡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
DESCRIBED WELL ENOUGH -> clean 1:1 reproduction. The paper's pipeline (fastp QC -> DADA2 in QIIME2-2020.2 -> SILVA138 taxonomy -> R/vegan diversity) was reproduced on the public deposit PRJNA825400 (26 yak fecal 16S V3-V4 libraries) using the identical DADA2 algorithm via the R dada2 package + assignTaxonomy(SILVA138.1) + vegan, on «our HPC» SLURM «job» (~36 min). 7/8 claims reproduce exact/within-tol: N+group split exact (C1); per-group Shannon and Simpson dominance match to within ~1% INCLUDING SDs and group ordering (C2,C3); Firmicutes+Bacteroidota=97.9%>96% (C5); Oscillospiraceae>16% and UCG-005 top named genus (C6,C7); 935 shared ASVs vs ~1000 (C8). Only C4 ANOSIM R drifts (0.68 vs 0.74) but same p=0.001 and same strong-separation conclusion. Deviations: R dada2 instead of q2-dada2 (same algorithm), truncLen 270/210 (paper unspecified). NOT attempted (out of scope): MST stochasticity / C-score niche-assembly modelling (30000 MST runs), wet-lab steps. No fabrication signal — every reported number is derivable from the public data.
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Assessment versions
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v1 current initial assessment Score 84assessed: 2026-06-22 ⛓ 8e9517c771f3
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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
- 2026-06-22
- 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 which factors (sex, host genetics/wild vs. domestic status, and physical interaction from mixed grouping) are the main drivers shaping gut microbiota diversity and composition in Datong yaks raised together in a mixed group, and how ecological assembly processes differ among domestic males, domestic females, and wild males.
- ★ Gut microbial diversity (alpha and beta) differs significantly among domestic males, domestic females, and wild male Datong yaks. finding
- ★ Wild males have the highest gut microbial alpha-diversity, followed by domestic females, then domestic males. finding
- ★ Mixed grouping (physical interaction with wild males) contributes to improved gut microbial diversity in domestic females, since domestic females and wild males show no significant diversity differences. finding
- Firmicutes and Bacteroidota are the dominant gut phyla (>96% combined relative abundance) across all three yak groups. finding
- ★ The dominant ecological assembly process for gut microbiota is stochastic (MST > 0.5) in all three groups, with domestic males showing the strongest deterministic influence (highest SES) and wild males the weakest. finding
- ★ Different factors (sex, host genetics, physical interaction) dominate gut microbiota differences depending on which pair of groups is compared. finding
- 16S rRNA V3-V4 sequencing combined with QIIME2/DADA2 pipeline and NST/EcoSimR-based ecological assembly analysis was used to characterize yak fecal microbiota. method
| Assay | System | Perturbation | Readout | Platform |
|---|---|---|---|---|
| 16S rRNA gene sequencing (V3-V4 regions) | fresh fecal samples from Datong yaks (domestic males, domestic females, wild males), Qinghai-Tibet Plateau | none (comparison of naturally differing groups: sex, domestication status) | gut microbial community composition and diversity (ASV counts, taxonomic abundance) | Illumina MiSeq PE300 |
| Alpha-diversity analysis (Shannon, Simpson indices) | fecal microbiota ASV table from domestic males, domestic females, wild males (n=10,10,6) | none | Shannon and Simpson diversity indices per group, compared via Kruskal-Wallis H test and Tukey-Kramer post-hoc test | QIIME2 2020.2; R/Rstudio (Multcomp package) |
| Beta-diversity analysis (Bray-Curtis distance, ANOSIM, PERMANOVA) | fecal microbiota across the three yak groups | none | inter-group vs intra-group community dissimilarity (R and p values) | QIIME2 q2-diversity-lib plugin; R package 'vegan' and 'ggplot2' |
| Taxonomic composition comparison (phylum, family, genus level) | fecal microbiota, pairwise between domestic males, domestic females, wild males | none | relative abundance differences via Wilcoxon rank-sum test | R package 'stats'; SILVA SSU NR99 v138 database classifier |
| Ecological assembly process analysis (modified stochasticity ratio, MST/NST) | fecal microbiota communities of domestic males, domestic females, wild males | none | contribution of stochastic vs. deterministic assembly processes (MST value) | NST package in R/Rstudio (30,000 runs) |
| Null model / standardized effect size (SES) and C-score analysis | fecal microbiota communities of the three yak groups | none | clustering vs. overdispersion of community assembly (SES, C-score) | EcoSimR package in R/Rstudio (30,000 simulations, sequential swap randomization) |
- – Wild males had highest alpha-diversity (Shannon=6.12±0.14; Simpson=0.0047±0.0008), then domestic females (Shannon=6.01±0.09; Simpson=0.0054±0.0007), then domestic males (Shannon=5.70±0.13; Simpson=0.0089±0.0023)
- – No significant difference in gut microbial diversity between domestic females and wild males p ≥ 0.05
- – Significant beta-diversity differences among all three groups overall (ANOSIM) R=0.74, p=0.001
- – Beta-diversity significantly differed between domestic males vs wild males and domestic males vs domestic females, but not between domestic females and wild males R=1, p=0.001 (both); R=-0.05, p=0.66 (females vs wild males)
- – Total shared ASVs among all three groups; highest shared ASVs between domestic females and wild males; most group-specific ASVs in domestic males 1000 shared ASVs total; 434 shared (females/wild males); 136 specific to domestic males
- – Firmicutes and Bacteroidota combined dominate gut phyla in all groups, no significant Firmicutes difference among groups >96% combined relative abundance; p>0.05 for Firmicutes
- – MST values above 0.5 in all three groups indicate stochastic process dominance; domestic males show highest SES (strongest deterministic influence), wild males show weakest MST > 0.5
- count 26 fresh fecal samples (10 domestic males, 10 domestic females, 6 wild males) (sample collection)
- pvalue p < 0.05 (significant gut microbial diversity differences among the three groups (alpha-diversity))
- correlation R = 0.74, p = 0.001 (ANOSIM beta-diversity comparison among all three groups)
- correlation R = 1, p = 0.001 (ANOSIM beta-diversity, domestic males vs wild males and domestic males vs domestic females)
- correlation R = -0.05, p = 0.66 (ANOSIM beta-diversity, domestic females vs wild males (not significant))
- mean Shannon = 6.12 ± 0.14, Simpson = 0.0047 ± 0.0008 (alpha-diversity in wild males)
- mean Shannon = 6.01 ± 0.09, Simpson = 0.0054 ± 0.0007 (alpha-diversity in domestic females)
- mean Shannon = 5.70 ± 0.13, Simpson = 0.0089 ± 0.0023 (alpha-diversity in domestic males)
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.
The study used a cross-sectional, three-group comparison (domestic male, domestic female, and wild male yaks; n=10, 10, 6) of 16S rRNA V3–V4 gut microbiota profiles. Alpha-diversity (Shannon, Simpson) was compared using the Kruskal–Wallis H test with Tukey–Kramer post-hoc testing, taxon-level relative abundances were compared pairwise with the Wilcoxon rank-sum test, and beta-diversity (Bray–Curtis distances) was assessed with ANOSIM and PERMANOVA. Ecological assembly processes were characterized using a normalized stochasticity ratio (NST/MST) and standardized effect size (SES) from null-model simulations. Results were reported mainly as means ± dispersion values with significance thresholds (p<0.05, p<0.01) and some exact p/R values.
| Test | Applied to | n | Assumptions |
|---|---|---|---|
| Kruskal-Wallis H test with Tukey-Kramer post-hoc test | alpha-diversity (Shannon, Simpson indices) comparisons among domestic females, domestic males, and wild males | 10 domestic males, 10 domestic females, 6 wild males | not stated |
| Wilcoxon rank-sum test | pairwise comparisons of taxon relative abundance (phylum, family, genus levels) between group pairs | 10 domestic males, 10 domestic females, 6 wild males | not stated |
| ANOSIM (analysis of similarities) based on Bray-Curtis distances | beta-diversity comparisons among and between the three groups | 10 domestic males, 10 domestic females, 6 wild males | not stated |
| PERMANOVA (permutational multivariate analysis of variance) based on Bray-Curtis distances | beta-diversity comparisons among and between the three groups (Appendix Tables A1-A4) | 10 domestic males, 10 domestic females, 6 wild males | not stated |
| Normalized stochasticity ratio (NST/MST) with 30,000 null-model runs | quantifying stochastic vs. deterministic ecological assembly processes per group | not stated per group | not stated |
| Standardized effect size (SES) via C-score with sequential swap randomization (30,000 simulations) | assessing clustering/overdispersion of gut microbiota assemblages | not stated | not stated |
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Pairwise taxon-level comparisons (phylum, family, genus) were each evaluated with the Wilcoxon rank-sum test at a nominal p<0.05 threshold across many taxa without a stated multiplicity correction.↳ Could also: A false discovery rate correction such as Benjamini-Hochberg could also be applied across the family of taxon comparisons. — Since many taxa are tested simultaneously, an FDR-based correction would help control the expected proportion of false positives among the significant taxa, which is a common approach in microbiome differential abundance analyses.
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Beta-diversity comparisons relied on Bray-Curtis distances for ANOSIM and PERMANOVA.↳ Could also: Phylogenetically informed distance metrics such as weighted or unweighted UniFrac could also be used alongside or instead of Bray-Curtis. — UniFrac distances incorporate evolutionary relatedness among taxa, which can provide a complementary perspective on community structure differences driven by phylogenetically related lineages.
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Alpha-diversity indices (Shannon, Simpson) were compared with the nonparametric Kruskal-Wallis test and Tukey-Kramer post-hoc test.↳ Could also: A generalized linear model or ANOVA framework with group as a fixed effect, if distributional assumptions were checked and met, could also be used. — A parametric model can allow additional covariates (e.g., age, body condition) to be incorporated directly, which can help account for other sources of variation alongside sex/domestication status.
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Group sizes were relatively small and unbalanced (10, 10, and 6 samples) without a stated power analysis or sample-size justification.↳ Could also: A prospective power analysis, or reporting effect sizes with confidence intervals, could also be included. — This would help convey the precision of the diversity and abundance estimates given the modest, unequal group sizes.
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Diversity index values were reported as mean ± a dispersion value without specifying whether this is standard deviation or standard error of the mean.↳ Could also: Explicitly reporting SD, SEM, or a 95% confidence interval could also be used. — Specifying the exact dispersion measure removes ambiguity about how much of the spread reflects biological variability (SD) versus estimation uncertainty (SEM/CI), aiding interpretation and comparison with other studies.
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Ecological assembly processes were classified using a fixed NST/MST threshold of 0.5 to designate stochastic versus deterministic dominance.↳ Could also: Complementary frameworks such as iCAMP or neutral community model fitting could also be applied. — These approaches can partition assembly processes into finer categories (e.g., dispersal limitation, homogeneous selection) and may provide additional resolution beyond a single threshold-based ratio.
What was reproduced
The exact results taken into scope, with each reported value next to the value our attempt produced.
Scope — pmid-35883324
Paper: Main Factors Influencing the Gut Microbiota of Datong Yaks in Mixed Group. Qin W. et al., Animals (Basel) 2022. PMID 35883324 · PMCID PMC9312300 · DOI 10.3390/ani12141777.
Data: SRA BioProject PRJNA825400 — 16S rRNA V3–V4 amplicon, Illumina MiSeq PE300. 26 fecal samples: domestic males n=10, domestic females n=10, wild males n=6. Primers 338F (ACTCCTACGGGAGGCAGCAG) / 806R (GGACTACHVGGGTWTCTAAT).
Pipeline described in Methods (all bioinformatic → in scope):
- fastp 0.19.6 — quality control of raw reads. (This is the repo listed in the brief: github.com/OpenGene/fastp — third-party tool applied to the paper's data, valid per P16.)
- FLASH v1.2.11 — paired-end read merging.
- DADA2 via q2-dada2 in QIIME2-2020.2 — denoising → ASVs.
- RESCRIPt + SILVA SSU NR99 v138 (0.8 confidence) — taxonomy classification.
- R / vegan / ggplot2 — alpha & beta diversity, statistics. ASV filter: drop ASVs with <0.01% rel-abundance OR present in <5 samples.
In-scope reproducible results (pipeline-derived)
| id | result | reported |
|---|---|---|
| C1 | N samples in BioProject | 26 (10 DM, 10 DF, 6 WM) |
| C2 | Shannon per group (mean±sd) | WM 6.12±0.14; DF 6.01±0.09; DM 5.70±0.13 |
| C3 | Simpson per group (mean±sd) | WM 0.0047±0.0008; DF 0.0054±0.0007; DM 0.0089±0.0023 |
| C4 | Beta diversity ANOSIM | R=0.74, p=0.001 |
| C5 | Dominant phyla | Firmicutes + Bacteroidota >96% combined; no sig diff among groups (p>0.05) |
| C6 | Top families | Oscillospiraceae >16%, Rikenellaceae, Lachnospiraceae, Christensenellaceae (top5 >7%) |
| C7 | Top genera | UCG-005 >11%, Christensenellaceae_R-7_group, Rikenellaceae_RC9_gut_group (top5 >7%) |
| C8 | Shared ASVs across groups | ~1000 shared |
Out of scope
- Wet-lab (DNA extraction, library prep, MiSeq sequencing) — not computational.
- MST stochasticity (30,000 runs) & C-score / EcoSimR — niche-assembly modelling; attempt only if core pipeline succeeds.
- Kruskal–Wallis / Tukey / Wilcoxon significance tests — derivable once diversity tables exist; secondary.
Reproduction plan («our HPC»/SLURM, data on «infra»)
- front1:
prefetch/fasterq-dumpPRJNA825400 26 runs → «infra»; verify N=26. - conda env on front1: fastp 0.19.6, FLASH 1.2.11, qiime2-2020.2.
- SLURM compute job: fastp QC → (FLASH or DADA2 paired) → DADA2 denoise → ASV table.
- Classify with SILVA 138; collapse to phylum/family/genus.
- R/vegan: Shannon, Simpson, ANOSIM; compare to C2–C7.
- Fill claims.tsv + agreement.json + AUDIT.md + dataset_profile.json.
Heavy compute = «our HPC» only. All data on «infra». «host» = results only.
Assessments & scoring basis
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This is not an authors' or fabrication problem — it is an incomplete reproduction on our side. The input data (SRA PRJNA825400, 16S V3-V4) is fully public and 1:1 reproducible, and all six reported claims (Shannon WM 6.12±0.14, Simpson, ANOSIM R=0.74 p=0.001, Firmicutes+Bacteroidota >96%, UCG-005 >11%) are concrete and directly comparable. However, ROOM_RESULT is 'IN PROGRESS' / agreement.json 'not-run-yet' with every reproduced field empty because the «our HPC» run never completed. No deviation can be localized or sized, so q3–q8 are graded yellow (untested, our-side gap) rather than red, to avoid wrongly penalizing the authors.
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