Clock dating

How DNA accumulates changes
Contents:
  1. media-aid.com - Atmos Clock Dating
  2. Dating a longcase clock
  3. 1. Introduction
  4. Molecular clock

Many large datasets of fast-evolving viruses are not well fitted by molecular clock models that assume a constant substitution rate through time, and more flexible relaxed clock models are required for robust inference of rates and dates. Estimation of relaxed molecular clocks using Bayesian Markov chain Monte Carlo is computationally expensive and may not scale well to large datasets. We build on recent advances in maximum likelihood and least-squares phylogenetic and molecular clock dating methods to develop a fast relaxed-clock method based on a Gamma-Poisson mixture model of substitution rates.

media-aid.com - Atmos Clock Dating

This method estimates a distinct substitution rate for every lineage in the phylogeny while being scalable to large phylogenies. Unknown lineage sample dates can be estimated as well as unknown root position. We estimate confidence intervals for rates, dates, and tip dates using parametric and non-parametric bootstrap approaches. This method is implemented as an open-source R package, treedater.

Pathogen sequence data can provide important information about the timing and spread of infectious diseases, particularly for rapidly evolving pathogens such as RNA viruses. By using sampling dates in conjunction with sequence data, it is possible to estimate the rate of evolution, and hence generate phylogenetic trees calibrated in calendar time. While there may be a fairly constant average rate of evolution over epidemiological timescales, there may be variation in evolutionary rates across lineages in the phylogenetic tree; failure to account for this variation may lead to incorrect inferences of evolutionary rates and dates.

This has led to the development of computationally-intensive Bayesian approaches, which assume an underlying model for how evolutionary rates vary across the phylogeny Drummond et al. With the growth in the size of pathogen sequence datasets, it is becoming increasingly difficult to apply Bayesian relaxed-clock methods.

There have been several recent developments in fast, approximate methods for generating time-trees from sequence data To et al.

Dating a longcase clock

We present an approach to fit a relaxed clock to a non-clocklike phylogenetic tree with associated data on sampling times. Using simulated data, we demonstrate that explicit incorporation of a relaxed clock leads to more accurate inference of the mean rate of evolution in addition to providing information on the variation in evolutionary rates.


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Our implementation generates confidence intervals for the evolutionary rate and the time to the most recent common ancestor using parametric bootstrapping PB , which lends itself well to parallelization. Our approach allows testing of a relaxed vs. The data takes the form of a branch lengths b i in T with units of substitutions per site, which can be estimated from a sequence alignment using maximum likelihood ML , a Bayesian approach, or a distance-based approach such as neighbour joining.

Building timelines based on changes

We assume that the length of the sequence alignment, denoted S , is known. Following the approach in To et al. Minimizing RSS is linear in sample size. This is implemented using the quadratic-programming algorithms implemented in the mgcv and quadprog R packages Wood ; Turlach and Weingessel The main difference between this optimization and the one described in To et al.

We therefore adopt a fast heuristic iterative approach described in algorithm 1. This algorithm can be repeated for multiple starting conditions of the initial substitution rate to improve the quality of the estimate. Given a rooted tree T with branches in units of substitutions, x i will denote the root-to-tip RTT distance for sampled lineage i ; this is the sum of all branch lengths between the root node and tip i. A common approach to rate estimation is to regress x i on the known date of sampling t i.

1. Introduction

The slope of the regression line is an estimate of the mean rate of substitution per unit time where the correlation due to shared ancestry has been neglected. This approach is implemented in the software TempEst Rambaut et al. We adapt the approach implemented by the rtt function which is part of the ape R package McCloskey In brief, given a proposed root edge u , the residual sum of squares of the RTT regression using the tree rooted on u can be computed.

This can be repeated for every branch in the tree. The treedater algorithm uses this heuristic approach to identify a set of n r good candidates for the root position. Algorithm 1 can be repeated for every good candidate root position and the dated tree with the highest likelihood is returned. The complete algorithm is described in algorithm box 2.

This univariate optimization is then repeated for each uncertain tip date t i at each iteration k. Note that this is a heuristic optimization and in general will not return the unique optimal combination of tip and internal node dates. Better optima can be found by repeating the treedater algorithm with different guesses of the initial tip dates.

The performance of this tip-dating variant of the treedater algorithm is explored in simulation results below. Because the likelihood under the treedater model is optimized heuristically, it is challenging to apply standard likelihood based approaches such as profiling to estimate confidence intervals.


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A standard approach for assessing uncertainty in phylogenetic analyses is to perform non-PB, in which columns in the multiple sequence alignment are resampled with replacement in order to generate new datasets. Fast approximations to non-PB for phylogenetic reconstruction have also been proposed Nguyen et al. In addition to running treedater on multiple bootstrapped phylogenies, Monte Carlo simulation and PB approaches offer a highly flexible and parallelizable approach for estimating uncertainty in substitution rates and node dates Efron and Tibshirani The PB approach implemented in treedater assumes 1, the data were generated under the strict or relaxed clock model as implemented in treedater, so that substitutions on each branch will follow a NB distribution as in equation 1.

The treedater algorithm provides several statistics associated with each sampled lineage that can be useful for identifying outlier lineages; these may represent sequencing error or samples that are poorly described by the fitted substitution model. In such cases, outliers can be identified and removed in order to produce a data set that the given molecular clock model can better fit.

Existing software, such as TempEst Rambaut et al. For each sampled lineage treedater provides 1, the estimated log likelihood of the branch length under the substitution model; 2, the estimated substitution rate for that branch; 3, a P -value for the branch length under the fitted substitution model; and 4, a q-value Benjamini and Hochberg ; Benjamini and Yekutieli , which provides a quantitative measure of the extent to which the lineage is an outlier under the fitted model and adjusts for multiple testing bias. A strict clock is unlikely to hold in principle; in practice, however, there may be insufficient information in order to fit a relaxed clock.

We propose a simple frequentist test to reject the null hypothesis of a strict clock by computing the null distribution of the coefficient of variation CV of rates across the tree. The test utilizes the PB described in Section 2. First, the treedater algorithm is fit to the data under a strict clock Poisson substitution model. Then, the PB from Section 2. This provides a bootstrap distribution of estimated CV of rates under the null hypothesis that the clock is strict. Finally, the relaxed clock model is fitted to the original data set and the CV is estimated.

If the CV under the relaxed clock falls outside a pre-specified quantile of the bootstrap distribution, the null is rejected.

Molecular clock

To compare the performance of treedater with other dating methods, we use simulations from two recent publications To et al. The reader is referred to the original publications for a detailed description of simulation design; brief descriptions of the simulated datasets are as follows.

In To et al. Four scenarios are developed corresponding to different distributions of sample dates through time and different levels of within-host genetic diversity. Jones and Poon conducted a birth-death simulation to generate a genealogy and assume a strict molecular clock. For simulations in To et al. Though there is no known published reference books that date or 'grade' Atmos Clocks based on age or condition, the Chart below may be helpful in determining the age of your Atmos Clock.

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