Under the clock dating
Molecular clock models relate observed genetic diversity to calendar time, enabling estimation of times of common ancestry.
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.
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, Pathogen sequence data can provide important information about the timing and spread of infectious diseases, particularly for rapidly evolving pathogens such as RNA viruses.
This approach is implemented in the software good candidates for the root position.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 -value for the branch length under the fitted substitution model; and 4, a q-value (Benjamini and Hochberg 1995; Benjamini and Yekutieli 2001), 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.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.