scholarly journals Shedding light on the underlying characteristics of genomes using Kronecker model families of codon evolution

2020 ◽  
Author(s):  
Maryam Zaheri ◽  
Nicolas Salamin

AbstractThe mechanistic models of codon evolution rely on some simplistic assumptions in order to reduce the computational complexity of estimating the high number of parameters of the models. This paper is an attempt to investigate how much these simplistic assumptions are misleading when they violate the nature of the biological dataset in hand. We particularly focus on three simplistic assumptions made by most of the current mechanistic codon models including: 1) only single substitutions between nucleotides within codons in the codon transition rate matrix are allowed. 2) mutation is homogenous across nucleotides within a codon. 3) assuming HKY nucleotide model is good enough at the nucleotide level. For this purpose, we developed a framework of mechanistic codon models, each model in the framework hold or relax some of the mentioned simplifying assumptions. Holding or relaxing the three simplistic assumptions results in total to eight different mechanistic models in the framework. Through several experiments on biological datasets and simulations we show that the three simplistic assumptions are unrealistic for most of the biological datasets and relaxing these assumptions lead to accurate estimation of evolutionary parameters such as selection pressure.

2015 ◽  
Author(s):  
Kathryn A Massana ◽  
Jeremy M Beaulieu ◽  
Nicholas J Matzke ◽  
Brian C O'Meara

Historical biogeography seeks to understand the distribution of biodiversity in space and time. The dispersal-extinction-cladogenesis (DEC) model, a likelihood-based model of geographic range evolution, is widely used in assessing the biogeography of clades. Robust inference of dispersal and local extinction parameters is crucial for biogeographic inference, and yet a major caveat to its use is that the DEC model severely underestimates local extinction. We suggest that this is mainly due to the way in which the model is constructed to allow observed species to transition into being present in no areas (i.e., null range). By prohibiting transitions into the null range in the transition rate matrix, we were able to better infer local extinction and support this with simulations. This modified model, DEC*, has higher model fit and model adequacy than DEC, suggesting this modification should be considered for DEC and other models of geographic range evolution.


2015 ◽  
Vol 295 ◽  
pp. 639-644 ◽  
Author(s):  
Benjamin R. Betzler ◽  
Brian C. Kiedrowski ◽  
Forrest B. Brown ◽  
William R. Martin

1986 ◽  
Vol 35 (2) ◽  
pp. 192-200 ◽  
Author(s):  
Giuseppe Cafaro ◽  
Francesco Corsi ◽  
Francesco Vacca

Author(s):  
Yue Liu ◽  
Zhiyan Shi ◽  
Ying Tang ◽  
Jingjing Yao ◽  
Xincheng Zhu

This paper establishes a new version of integration by parts formula of Markov chains for sensitivity computation, under much lower restrictions than the existing researches. Our approach is more fundamental and applicable without using Girsanov theorem or Malliavin calculus as did by past papers. Numerically, we apply this formula to compute sensitivity regarding the transition rate matrix and compare with a recent research by an IPA (infinitesimal perturbation analysis) method and other approaches.


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