| Title || ThetaMater |
| Short Description || ThetaMater is an open source R package for Bayesian estimation of the population parameter theta from genomic data and conducting posterior predictive simulation of population genomic data under the infinite sites model. |
| Long Description || The R package ThetaMater provides a Bayesian framework to simulate posterior probability distributions of θ. At the core of ThetaMater is the infinite-sites likelihood function described in Watterson, 1975 and Tavaré, 1984, which describes the probability distribution of observing k mutations in a sample size of n sequences obtained from a locus with size l (see manual for model description). Integral to ThetaMater is a suite of functions for simulating population genetic data under the infinite sites model, given theta. These functions are used to simulate realistic datasets under the neutral coalescent model, which can be used to identify potential paralogous loci using posterior predictive simulation. With these simulated data, users can identify loci with unexpected patterns (i.e., unlikely mutation counts) of genetic variation. Furthermore, Thetamater includes several functions for simulating datasets that have evolved under models of among-site variation across the genome. |
| Version || 0.1.3 |
| Project Started || 2017 |
| Last Release || 3 years, 4 months ago |
This simulator has not yet been evaluated for GSR Certification. Learn more about or request GSR Certification.
|Author verification||The basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator.|