The Gibbs and splitmerge sampler for population mixture analysis from genetic data with incomplete baselines

By J. Pella, M. Masuda. 2006

111 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Genetics, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/8e97a24522552bae8812242a75037844095f103e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Daniel Falush
2. André E. Punt
3. Daniel J. Lawson
4. Eric C. Anderson
5. Garrett Hellenthal
6. Steven T. Kalinowski
7. Robin S. Waples
8. S. Myers

In Genetics

1. Robin S. Waples
2. André E. Punt
3. J. Cope
4. Daniel Falush
5. Daniel J. Lawson
6. Eric C. Anderson
7. Garrett Hellenthal
8. Steven T. Kalinowski

In Mathematical Physics

1. Daniel Falush
2. Daniel J. Lawson
3. Eric C. Anderson
4. Garrett Hellenthal
5. Steven T. Kalinowski
6. Robin S. Waples
7. S. Myers

Citations in the corpus

• Integrating genetic data into management of marine resources: how can we do it better? (2008, background): “In the current decade, much more powerful and much more general genetic clustering programmes have been developed (Pritchard et al. 2000; Corander et al. 2004; Pella and Masuda 2006) which do not require any baseline data at all.”
• Inference of Population Structure using Dense Haplotype Data (2012, methodology): “Although powerful, these approaches have drawbacks – determination of K is difficult despite some technical advances [18,19], and typically Kv10 is required for satisfactory convergence, due to issues of computational cost and the presence of distinct local optima, affecting even the fastest methods”
• CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure (2007, unknown): “…of individuals—to clusters (Anderson and Thompson, 2002; Chen et al. , 2006, 2007; Corander and Marttinen, 2006; Corander et al. , 2003, 2004; Dawson and Belkhir, 2001; Falush et al. , 2003; Franc¸ois et al. , 2006; Huelsenbeck and Andolfatto, 2007; Pella and Masuda, 2006; Pritchard et al. , 2000).”
• Clumpak: a program for identifying clustering modes and packaging population structure inferences across K (2015, unknown): “…& Belkhir 2001; Corander et al. 2003, 2004, 2008a,b; Falush et al. 2003, 2007; Guillot et al. 2005; Tang et al. 2005; Franc (cid:1) ois et al. 2006; Pella & Masuda 2006; Chen et al. 2007; Gao et al. 2007; Huelsen-beck & Andolfatto 2007; Guillot 2008; Alexander et al. 2009; Durand et al. 2009;…”
• An improved method for predicting the accuracy of genetic stock identification (2008, methodology): “Although the unconditional likelihood framework for GSI (Smouse et al. 1990) and Bayesian methods ( Pella and Masuda 2001, 2006 ) may be preferable to a conditional likelihood analysis, the conditional likelihood framework is usually used for analyzing the simulated data sets because it is customary”