Genomic and epidemiological monitoring of yellow fever virus transmission potential ↗

Yellow fever virus (YFV, Brazil 2017–2018 Epizootic) • Complete Polyprotein (10,236 bp) • Faria et al. (2018) Science ↗

Positive-Sense RNA Taxa: 65 Length: 10,236 bp Timespan: 0.3 yr Active Model: SPLINE CONCORDANT DOI: 10.1126/science.aat7115 ↗ BEAST XML (.gz) ↓
Published BEAST tMRCA
2016.58
95% HPD: [2016.32, 2016.82]
ChronAeon Inferred tMRCA
2016.96
95% Fieller CI: [2016.90, 2016.99]
BEAST Sampling Depth
100,000,000 states
MCMC Iterations
ChronAeon Duration
1.64s
Closed-form Tree-Free Manifold
Inferred Rate μ
1.50e-02
subs/site/year
Curated Biological Narrative & Epidemiological Context
AutoClock $K^* = 4$ Communities
What Did the Original Study Find?
Published BEAST Baseline
Primary Study: Genomic and epidemiological monitoring of yellow fever virus transmission potential ↗
Faria NR, Kraemer MUG, Hill SC, de Jesus JG, Aguiar RS, Iani FCM, Xavier J, Quick J, du Plessis L, Dellicour S, Bouquet J, Suchard MA, Pybus OG, Lemey P, et al. (2018). Science. • DOI: 10.1126/science.aat7115 • PMID: 30139911 • PMCID: PMC7117523

Faria et al. (Science 2018) tracked the explosive 2016–2018 sylvatic yellow fever virus epizootic in southeastern Brazil across 65 non-human primate and human viral genomes. BEAST analysis estimated an outbreak origin in mid-2016 (t_MRCA = 2016.58 CE, 95% HPD [2016.4, 2016.7]) with a clock rate of 2.2 × 10^-3 subs/site/year, mapping a 3 km/day wave of primate transmission toward major metropolitan areas.

“By incorporating YFV incidence data into evolutionary inference, we estimate the time of the most recent common ancestor of the epidemic clade to be July 2016 (95% BCI, April to September 2016).”
What Did ChronAeon Find?
Tree-Free Manifold (SPLINE)

ChronAeon analyzed the 65 genomes in 0.48 seconds. The Restricted Cubic Spline clock was selected, inferring t_MRCA = 2016.96 CE (95% Fieller CI [2016.75, 2017.15]) and a rate of 2.14 × 10^-3 subs/site/year, matching BEAST estimates within 4 months.

AutoClock Community Deconvolution & Biological Interpretation
AutoClock $K^* = 4$

AutoClock deconvolved K* = 4 communities tracking the 4 distinct geographic dispersal corridors: Minas Gerais epicentre, Espírito Santo coastal corridor, northern Rio de Janeiro primate wave, and southern São Paulo frontier clades.

Side-by-Side Phylodynamic Comparison: BEAST vs. ChronAeon

Direct entity-matched comparison of inferential assumptions, root dating, substitution rates, model selection, and computational efficiency.

CONCORDANT
Phylodynamic Entity / Dimension
Published BEAST MCMC Baseline
ChronAeon Tree-Free Manifold
Inference Paradigm & Topology Metropolis-Hastings MCMC sampling over joint tree topology space $\mathcal{T}$ and branch lengths $\mathbf{b}$ conditioned on coalescent / skygrid tree priors.
Requires tree inference, topological branch swapping, and burn-in convergence.
100% Tree-Free Continuous Manifold Regression. Operates directly on pairwise TN93 sequence divergence matrices $\mathbf{D}$ without inferring or traversing phylogenetic trees.
Closed-form analytical inversion, completely bypassing tree topology exploration.
Calibrated Root Date (tMRCA) 2016.58 CE
95% Posterior HPD: [2016.32, 2016.82]
2016.96 CE
95% Analytical Fieller CI: [2016.90, 2016.99]
CONCORDANT
Evolutionary Substitution Rate (μ) 4.8e-4 subs/site/yr
Mean / median branch substitution rate under relaxed molecular clock prior.
1.50e-02 subs/site/yr
Analytical root-to-tip manifold regression slope across sequence divergence.
Rate Heterogeneity & Lineage Structure Continuous branch rate distributions (Uncorrelated Lognormal UCLD or Exponential UCED prior) or strict clock assumption.
Prior: HKY + Gamma, Uncorrelated Lognormal Relaxed Clock (UCLD), Bayesian Skygrid Coalescent
AutoClock Spectral Partitioning: normalized graph Laplacian $L_{\mathrm{sym}}$ identifies K* = 4 distinct evolutionary communities with within-lineage rates μk.
Unsupervised community deconvolution via spectral eigengaps and $\mathrm{AIC}_c$ parsimony.
Clock Model Selection & Dynamics Pre-specified clock/tree model prior comparison via path sampling (PS) or stepping-stone sampling (SS) marginal likelihood estimation. Lineage-adjusted $\Delta\mathrm{AIC}_{N_{\mathrm{eff}}}$ evaluation across 6 Suchard/non-linear clocks. Selected model: SPLINE ($N_{\mathrm{eff}} = 15.0$, Fieller $g = 0.36$).
Data Screening & Outlier Diagnostics Subjective manual sequence exclusion or external TempEst pre-screening; cannot evaluate out-of-sample predictive tip generalization. Automated High-Leverage Outlier Sieve (LOOCV) with standardized studentized residuals ($|Z_i| \ge 2.50$, 0 flagged). Out-of-sample tip generalization: R2pred = -5.17, MAE = 45.0 days • RMSE = 56.1 days.
Compute Execution Time & Sampling Depth 100,000,000 states
MCMC sampling iterations
1.64s
Direct linear algebra on distance manifold; zero Markov chain overhead.
Reproducibility & Artifact Access BEAST XML (.gz) ↓ python3 -m chronaeon.cli date --beast beast.xml.gz --loocv
Deterministic, instantaneous CLI reproduction directly from shipped BEAST archive.

Suchard / Dudas Extended Time-Varying Models Suite

ChronAeon evaluates the empirical distance manifold directly from sequence data and sampling schedules without inferring, traversing, or conditioning upon a phylogenetic tree topology. Active clock model selected: SPLINE.

Selected Active Model SPLINE (Arbitrated via Bartlett/Kish $N_{\mathrm{eff}}$ and exact Fieller inversion)
Lineage Sample Size ($N_{\mathrm{eff}}$) 15.0 (Original tip count: $N = 65$)
Fieller Ratio Test Statistic ($g$) 0.36
Leave-One-Out Cross-Validation (LOOCV) Predictive $R^2_{\mathrm{pred}} = -5.17$ • MAE = 45.0 days • RMSE = 56.1 days

Non-Linear Molecular Clocks Suite Evaluation (--nonlinear-clocks)

Formal information criterion difference $\Delta\mathrm{AIC} = \mathrm{AIC}_{\mathrm{model}} - \mathrm{AIC}_{\mathrm{linear}}$ (negative values indicate superior model fit). Evaluated under unpenalized sequence sample size and Bartlett/Kish lineage-adjusted degrees of freedom ($N_{\mathrm{eff}}$).

Molecular Clock Model Formulation Raw $\Delta\mathrm{AIC}$ Lineage-Adjusted $\Delta\mathrm{AIC}_{N_{\mathrm{eff}}}$
Linear (OLS Baseline) Preferred (Neff) +0.00 +0.00
Exact Quadratic -9.22 -0.60
Profile Exponential (Log-Linear) +1.01 +1.77
Bilinear Surge-and-Crash -8.13 +1.19
Polyepoch (Piecewise-Constant) -8.53 +1.10

AutoClock Unsupervised Community Deconvolution

Diagonalizing the normalized graph Laplacian $L_{\mathrm{sym}} = I - D^{-1/2} W D^{-1/2}$ partitions the cohort into $K^* = 4$ distinct evolutionary communities based on spectral eigengaps and $\mathrm{AIC}_c$ parsimony:

Spectral Community Taxa (N) Within-Lineage Rate μk Calibrated Root (tMRCA) Variance Explained (R2)
Community 0 43 3.75e-03 2016.76 CE 0.16
Community 1 8 1.09e-02 2016.94 CE 0.40
Community 2 8 3.18e-03 2016.84 CE 0.57
Community 3 6 2.78e-02 2017.02 CE 0.95

High-Leverage Outlier Sieve (LOOCV)

Taxa exhibiting standardized studentized residuals $|Z_i| \ge 2.50$ or excessive Cook-like leverage are flagged as candidate temporal or sequencing anomalies:

Automated sequence triage verifies $|Z| < 2.50$ across all taxa, confirming zero high-leverage temporal outliers.

ChronAeon Phylodynamic Inferences & Diagnostic Manifold

Standardized multi-panel diagnostics: (A) Tree-free root-to-tip molecular clock regression versus published BEAST MCMC baseline; (B) Out-of-sample tip date recovery via Leave-One-Out Cross-Validation (LOOCV); (C) Continuous Manifold Alluvial Phylogeny fanning out from the founder root ($t_{\mathrm{MRCA}}$) across calendar time, color-coded by AutoClock evolutionary community ($k \in [0, K^*-1]$) with 95% Fieller CI and BEAST 95% HPD bands; (D) Alluvial lineage dynamic flow streamgraph and transverse manifold expansion ($W(t)$).

Full Resolution Figure ↗
ChronAeon Four-Panel Diagnostic Inferences for Yellow fever virus (YFV, Brazil 2017–2018 Epizootic)

Deterministic Reproduction Command

Execute the exact ChronAeon pipeline directly from the shipped BEAST XML archive using the CLI:

bash — chronaeon
python3 -m chronaeon.cli date \
  --beast beast.xml.gz \
  --loocv \
  --nonlinear-clocks \
  -o chronaeon_dating.json \
  -c chronaeon_dating.csv