A Spatial Statistical Model for Landscape Genetics

By Gilles Guillot, Arnaud Estoup, F. Mortier, J. Cosson. Genetics, 2005

696 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/97cfd7ff3260a2274400d8bb6cde076d665037ee

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

Modeling connectivity of black bears in a desert sky island archipelago (2011, methodology): “The assignment of individuals to subpopulations was performed in a separate run as suggested by Guillot et al. (2005a).”
Analysing georeferenced population genetics data with Geneland: a new algorithm to deal with null alleles and a friendly graphical user interface (2008, methodology): “To assess the beneﬁt of using this extra step, we produced data according to the model implemented for simulations in Geneland.”
Detecting loci under selection in a hierarchically structured population (2009, methodology): “Uncertainty about population structure We assume here that the genetic structure of the population is known in advance, but when this is not the case several approaches could be used to define this genetic structure from the data (for example, Pritchard et al., 2000; Dupanloup et al., 2002; Corander”
Landscape genetics: where are we now? (2010, methodology): “Bayesian assignment methods were also frequently used for genetic clustering purposes, and the use of spatial assignment tests, in particular, has increased over time, likely because of the increased availability of software (e.g. Geneland, Guillot et al. 2005; Spatial BAPS, Corander et al. 2007).”
Ecological genetics of invasive alien species (2011, methodology): “The spatial domain occupied by inferred clusters can be examined to identify dispersal barriers, using programmes such as GENELAND (Guillot et al. 2005b), and genetic diversity can be simulated, accounting for environmental and spatial heterogeneity, using software such as SPLATCHE (Currat et al. 20”
Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study (2007, background): “Hence the power of geneland does not seem to rest on its ability to detect recent immigrants as claimed in (Guillot et al. 2005) and (Excoffier & Heckel 2006).”
Bayesian spatial modeling of genetic population structure (2008, methodology): “For instance, Gelfand and Vounatsou (2003) used a fixed Voronoi tessellation to specify a neighborhood structure for the spatial domain of the sample, whereas Guillot et al. (2005) modelled the domain by using a tessellation in which the number, shapes and locations of the cells were all random.”
Visualizing spatial population structure with estimated effective migration surfaces (2014, methodology): “Among these, admixture-based clustering [14, 15, 16] and principal components analysis (PCA) [17, 18] are most widely used.”
Why sampling scheme matters: the effect of sampling scheme on landscape genetic results (2009, background): “…et al. 2003, 2007), although other approaches and programs exist (e.g., PARTITION, Dawson and Belkhir 2001; BAPS2, Corander et al. 2004; GENELAND, Guillot et al. 2005a, b; 2D LSA in GEN- ALEX, Double et al. 2005, Peakall and Smouse 2006; HMRF models, François et al 2006; TESS Chen et al. 2007).”
Using spatial Bayesian methods to determine the genetic structure of a continuously distributed population: clusters or isolation by distance? (2009, methodology): “Recent advances explicitly address the spatial nature of the problem of locating genetic discontinuities by including the geographical coordinates of individuals in their prior distributions (e.g., Guillot et al. 2005; Corander, Sirén & Arjas 2008).”
Hierarchical and Spatially Explicit Clustering of DNA Sequences with BAPS Software (2013, background): “Several spatial models for estimating genetic population structure from molecular marker loci have been introduced in the past few years (Wasser et al. 2004; Guillot et al. 2005; Francois et al. 2006; Chen et al. 2007; Corander et al. 2008b).”
Circuit Theory and Model-Based Inference for Landscape Connectivity (2013, positive): “Spatial clustering methods (e.g., Guillot et al. 2005; Chen et al. 2007; Durand et al. 2009) are commonly used to identify genetic boundaries, but are typically based on the assumption of a homogeneous underlying landscape, with any link to the underlying landscape made post hoc (e.g., Wheeler,…”
Revealing cryptic spatial patterns in genetic variability by a new multivariate method (2008, methodology): “Contrary to other spatially explicit methods (Dupanloup et al., 2002; Guillot et al., 2005), we do not impose a specific connection network; one would have to choose from existing algorithms, and refine it according to what is known about the ecological connectivity in the system.”
Putting the ‘landscape’ in landscape genetics (2007, methodology): “One distinct benefit of a landscape genetics approach is that spatially explicit techniques can allow researchers to identify barriers not detectable by traditional population genetic methods (Guillot et al., 2005a; Coulon et al., 2006).”
Inference of Population Structure using Dense Haplotype Data (2012, neutral): “[2,11–17]).”
Integrating genetic data into management of marine resources: how can we do it better? (2008, background): “landscape genetics – the study of spatial genetic patterns in continuously distributed species – is rapidly evolving (Manel et al. 2003; Guillot et al. 2005).”
Geneland: a computer package for landscape genetics (2005, methodology): “Guillot et al. (2005) have described the spatial statistical model and Markov Chain MonteCarlo technique used for inferences, and they thoroughly tested, from simulated datasets, the efficiency of the method to estimate the number of populations, assign individuals to populations of origin, map the…”
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, methodology): “We used structure as a representative of this type of analysis, but this is an active area of research and several other competing programs are available (e.g. Dawson & Belkhir 2001; Corander et al. 2004; Guillot et al. 2005).”