Genetic assignment methods for the direct, real‐time estimation of migration rate: a simulation‐based exploration of accuracy and power

By D. Paetkau, Rob W. Slade, M. Burden, Arnaud Estoup. Molecular Ecology, 2004

1,535 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e47874ce017a4846d5d2b210e25ff22e34168956

How researchers see this paper

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

In Genetics

Citations in the corpus

Integrating genetic data into management of marine resources: how can we do it better? (2008, background): “Conversely, when migrants are numerous, perhaps near the proportion required to produce demographic coupling, they will be genetically similar to resident individuals and thus difficult to detect using genetic markers (Paetkau et al. 2004; Manel et al. 2005).”
Ecological investigations of grizzly bears in Canada using DNA from hair, 1995–2005: a review of methods and progress (2010, methodology): “Although several assignment methods determine migrant significance based on simulations (Rannala and Mountain 1997), we recommend the routine developed by Paetkau et al. (2004) because it uses an improved simulation to produce accurate Type I error rates.”
Efficiency of markers and methods for detecting hybrids and introgression in stocked populations (2009, methodology): “We also used the ‘simulation option’ of Paetkau et al. (2004) for assessing the probability of each individual being rejected from the reference populations.”
GENECLASS2: a software for genetic assignment and first-generation migrant detection. (2004, methodology): “Note also that the computations based on the algorithm of Paetkau et al. (2004) are more time consuming than those based on the algorithm of Cornuet et al. (1999) or Rannala and Mountain (1997).”
A Spatial Statistical Model for Landscape Genetics (2005, neutral): “:3)”
Reconstructing routes of invasion using genetic data: why, how and so what? (2010, methodology): “Other methods are based on calculations of assignment likelihood (Ciosi et al. 2008; Genton et al. 2005; Paetkau et al. 2004; Pascual et al. 2007; Rannala & Mountain 1997; Tepolt et al. 2009; Thibault et al. 2009) or parsimony networks (e.g. Voisin et al. 2005; Hoos et al. 2010).”
INTRASPECIFIC GENETIC DIVERSITY IN THE MARINE COCCOLITHOPHORE EMILIANIA HUXLEYI (PRYMNESIOPHYCEAE): THE USE OF MICROSATELLITE ANALYSIS IN MARINE PHYTOPLANKTON POPULATION STUDIES 1 (2006, background): “Assignment tests (Paetkau et al. 2004) revealed that”
INVITED REVIEW: What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity (2006, background): “In some cases, assignment tests also have reasonable power to detect migrant individuals (Paetkau et al. 2004), and in principle this provides a basis for estimating a contemporary migration rate by taking advantage of naturally occurring ‘genetic marks’ of individuals.”
Gene flow and genetic structure of the aquatic macrophyte Sparganium emersum in a linear unidirectional river (2009, neutral): “AFLPs and microsatellites) (Berry, Tocher & Sarre, 2004; Paetkau et al., 2004; Manel, Gaggiotti & Waples, 2005).”
Do cities represent sources, sinks or isolated islands for urban wild boar population structure? (2017, methodology): “We followed a Bayesian approach (Rannala & Mountain 1997; Cornuet et al. 1999) applying the Monte Carlo resampling method with 10 000 simulated individuals (Paetkau et al. 2004) for multilocus genotypes, assuming an equal prior density of allelic frequencies at each locus in each population.”
Conceptual issues in local adaptation (2004, background): “…and underlying models, as well as their advantages and limitations have been repeatedly reviewed (Neigel 1997; Bossart & Prowell 1998; Ouborg et al. 1999; Sork et al. 1999; Paetkau et al. 2004; for an application in a context of local adaptation see, e.g. Mopper et al. 2000; Brown et al. 2001).”
dartr: An r package to facilitate analysis of SNP data generated from reduced representation genome sequencing (2018, methodology): “Assigning individuals of unknown provenance to populations of known provenance is a challenging exercise, and several approaches have been suggested (Blanchong, Scribner, & Winterstein, 2002; G € otz & Thaller, 1998; Manel, Gaggiotti, & Waples, 2005; Paetkau, Slade, Burden, & Estoup, 2004).”
Assignment methods: matching biological questions with appropriate techniques. (2005, background): “[ 6 ,12]), comparative analyses of performance of the various methods are lacking in most cases.”
What can genetics tell us about population connectivity? (2010, background): “With large sample sizes and numbers of variable loci, individuals can be correctly assigned even with low genetic divergence (Paetkau et al. 2004; Hall et al. 2009).”