domingo, 29 de noviembre de 2015

Phylogenetic inference and philosophy, different approaches for the same purpose


************** This post was updated on 27.01.2016***************


Phylogenetic inference attempts to elucidate the evolutionary relationships among organisms.
Various approaches have been made for this purpose, they differ in their rationale for addressing the problem (De Queiroz & Poe, 2001). Among the best known approaches are parsimony, bayesian inference and  likelihoodism. Below I will discuss some of its characteristics, basic assumptions and finally express which one, in my opinion, comes more adequately to face a phylogenetic analysis.

Parsimony has its grounds in the principle of simplicity. Proponents of the principle of parsimony argue that this approach is justified by the ideas of Karl Popper. This implies that the phylogenetic hypothesis must be falsifiable and  rigorous tests, so be corroborated. From this perspective, those hypotheses with the least amount of  changes should be preferred, thus minimizing the number of ad hoc explanations (Grupe & Harbeck, 2015). But the preference for simpler explanations does not mean that nature behaves well, evolution does not have to be parsimonious. This seems difficult to understand, and in fact, sounds contradictory.

Statistical approaches such as maximum likelihood or Bayesian inference share using evolutionary models that take into account the probability of  changes  between  character states and base frequencies (Archibald, Mort, & Crawford, 2003). In a parsimonious approach  seems that these changes are equally likely.

The likelihood method can be defined as the probability of a hypothesis given the data   of the data given a hypothesis. This approach seeks to find that hypothesis explains the observed data (characters) in the manner that maximizes the probability that these are observed.

Bayesian inference is different from the likelihood that takes into account prior knowledge to the observations,  it is posibe assign probabilities to hypotheses (Topologies) before observations are made. The main problem with the Bayesian inference is its distinguishing feature. The priors can be a double-edged sword, on the one hand allow the process to incorporate prior knowledge of phylogenetic inference, but actually priors are difficult to accurately estimate  (Velasco,2008). For several authors is a common practice then assign equal priors, but this means that the main advantage of this method had just wasted . Additionally, what if the priors are estimated incorrectly, this could result in a bias in the results of the process.

The advantages of statistical methods seem obvious, they make assumptions on a given model. Parsimony however, assumes any evolutionary model, or does this mean that the changes are equally likely, it does not seem logical, especially if we speak of continuous characters. Given these difficulties with the priors, in my opinion, a likelihoodism approach is most appropriate for phylogenetic inference.

References


  • Grupe, G., & Harbeck, M. (2015). Taphonomic and Diagenetic Processes. En W. Henke & I. Tattersall (Eds.), Handbook of Paleoanthropology (pp. 417–439).
  •  De Queiroz, K., & Poe, S. (2001). Philosophy and phylogenetic inference: a comparison of likelihood and parsimony methods in the context of Karl Popper’s writings on corroboration. Systematic Biology, 50(3), 305–321.
  • Archibald, J. K., Mort, M. E., & Crawford, D. J. (2003). Bayesian inference of phylogeny: a non-technical primer. Taxon, 187–191.
  • Velasco, J. D. (2008). Philosophy and The Tree of Life (Doctoral dissertation, Ph. D. Thesis). University of Wisconsin-Madison).

  




1 comentario:

Daniel Ernesto dijo...

The likelihood method can be defined as the probability of the data given a hypothesis