Molecular dating of phylogenetic trees is a growing discipline using sequence data to co-estimate the timing of evolutionary events and rates of molecular evolution. All molecular-dating methods require converting genetic divergence between sequences into absolute time.
Allows sequence manipulation and analysis in molecular biology, phylogenetics and evolution. DAMBE is a software that can extract the sequence upstream of each coding sequences (CDSs). It identifies the putative Dalgarno sequences (SDs) in all protein-coding sequences and outputs a variety of summary statistics to show which gene has a strong and optimally positioned SD/anti-SD (aSD). Moreover, it can indicate gene location in the output sequence file.
A cross-platform program for Bayesian phylogenetic analysis of molecular sequences. BEAST estimates rooted, time-measured phylogenies using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST 2 uses Markov chain Monte Carlo (MCMC) to average over tree space, so that each tree is weighted proportional to its posterior probability. BEAST 2 includes a graphical user-interface for setting up standard analyses and a suit of programs for analysing the results. It uses an XML input format that allows the user to design and run a large range of models. We also include a program that can convert NEXUS files into this format.
A package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). PAML may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (dN and dS) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations.
Uses parametric, nonparametric and semiparametric methods to relax the assumption of constant rates of evolution to obtain better estimates of rates and times. r8s permits users to convert results to absolute rates and ages by constraining one or more node times to be fixed, minimum or maximum ages (using fossil or other evidence). It uses truncated Newton nonlinear optimization code with bound constraints, offering superior performance over previous versions.
Analyzes and visualizes temporally sampled sequence data. TempEst examines temporal signal and ‘clocklikeness’ of molecular phylogenies. This application can perform reading and analysis of contemporaneous trees and dated-tip tree and can be utilized to explore isochronous phylogenies whose tips are sampled at the same time. It also suits to detect sequences whose sampling date is discordant with their genetic divergence and phylogenetic position.
Provides the workflow used to obtain whole-genome sequence data of 340 sequence type (ST) 772 Staphylococcus aureus isolates (the Bengal Bay clone). bengal-bay allows users to reproduce core analyses, including parameter settings, cluster resource configurations and versioned software distributions. The workflow implements Anaconda virtual environments, including software distributed in the Bioconda channel and is executable through Snakemake.
Estimates the dates of the internal nodes of a phylogenetic tree. node.dating is a divergence-time analysis software and uses a maximum-likelihood method. It can be extended to incorporate a variable molecular clock. The molecular clock assumption implies that mutations are strictly additive over time, which is not true. It may be possible to incorporate this ‘negative’ evolution into the model.