|
|
 |
| |
|
|
|
Parallel Metropolis Coupled Markov Chain Monte Carlo for Isolation with Migration Model |
|
|
|
PP: 219-224 |
|
|
|
Author(s) |
|
|
|
Chunbao Zhou,
Xianyu Lang,
Yangang Wang,
Chaodong Zhu,
Zhonghua Lu,
Xuebin Chi,
|
|
|
|
Abstract |
|
|
| Isolation with Migration model (IM), which jointly estimates divergence times and migration rates between two populations
from DNA sequence data, can capture many phenomena when one population splits into two. The parameters inferences for IM are
based on Markov Chain Monte Carlo method (MCMC). Standard implementations of MCMC are prone to fall into local optima.
Metropolis Coupled MCMC [(MC)3] as a variant of MCMC can more readily explore multiple peaks in posterior distribution of trees.
Expensive execution time has limited the application of (MC)3. This paper proposes a Parallel Metropolis Coupled Markov Chain
Monte Carlo for IM. The proposed parallel algorithm retains the ability of (MC)3 and maintains a fast execution time. Performance
results indicate nearly linear speed improvement. This paper provides researcher with rapider and more high-efficiency methods to
study population genetics and molecular ecology problems aided with super computer. |
|
|
|
|
|
|
|
