Rxivist logo

Measuring historical and compositional signals in phylogenetic data

By Lars S Jermiin, Bernhard Misof

Posted 03 Jan 2020
bioRxiv DOI: 10.1101/2020.01.03.894097

Most commonly-used molecular phylogenetic methods assume that the sequences evolved on a single bifurcating tree and that the evolutionary processes operating at the variable sites are Markovian. Typically, it is also assumed that these evolutionary processes were stationary, reversible and homogenous across the edges of the tree and that the multiple substitutions at variable sites occurred so infrequently that the historical signal (i.e., the signal in DNA that is due to the order and time of divergence event) in phylogenetic data has been retained, allowing for accurate phylogenetic estimates to be obtained from the data. Here, we present two metrics, λ and δCFS, to quantify the strength of the historical and compositional signals in phylogenetic data. λ quantifies loss of historical signal , with λ = 0.0 indicating evidence of a strong historical signal and λ = 1.0 indicating evidence of a fully eroded historical signal. δCFS quantifies compositional distance from full symmetry of a divergence matrix generated by comparing two sequences, with δCFS =0.0 indicating no evidence of evolution under dissimilar conditions and δCFS >0.0 indicating increasing evidence of lineages diverging under different conditions. The metrics are implemented in methods intended for use after multiple sequence alignment and before model selection and phylogenetic analysis. Results generated using these methods allow users of phylogenetic tools to select phylogenetic data more wisely than it previously was possible. The merits of these metrics and methods are illustrated using simulated data and multi-gene alignments obtained from 144 insect genomes.

Download data

  • Downloaded 312 times
  • Download rankings, all-time:
    • Site-wide: 92,477
    • In evolutionary biology: 4,819
  • Year to date:
    • Site-wide: 132,285
  • Since beginning of last month:
    • Site-wide: 140,708

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide