Nov 24, 2015

One-rate models outperform two-rate models in site-specific dN/dS estimation

BioRxiv : the Preprint Server for Biology
Stephanie SpielmanClaus O Wilke

Abstract

Methods that infer site-specific dN/dS, the ratio of nonsynonymous to synonymous substi- tution rates, from coding data have been developed primarily to identify positively selected sites (dN/dS > 1). As a consequence, it is largely unknown how well different inference methods can infer dN/dS point estimates at individual sites. In particular, dN/dS may be estimated using either a one-rate approach, where dN/dS is parameterized as a single parameter, or a two-rate approach, in which dN and dS are estimated separately. While some have suggested that the two-rate paradigm may be preferred for positive-selection inference, the relative merits of these two paradigms for site-specific dN/dS estimation remain largely untested. Here, we systematically assess how accurately several popular inference frameworks infer site-specific dN/dS values using alignments simulated within a mutation-selection framework rather than within a dN/dS-based framework. As mutation-selection models describe long-term evolutionary constraints, our simulation approach further allows us to study under what conditions inferred dN/dS captures the underlying equilibrium evolutionary process. We find that one-rate inference models universally outperform two-rate ...Continue Reading

  • References
  • Citations

References

  • We're still populating references for this paper, please check back later.
  • References
  • Citations

Citations

  • This paper may not have been cited yet.

Mentioned in this Paper

Animal Cancer Model
Supernumerary Maxillary Right Lateral Primary Incisor
Site
Simulation
Mutation Abnormality
Paradigm

About this Paper

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.