Geneland is a computer program for statistical analysis of population genetics data.
Its main goal is to detect population structure in form of systematic variation of allele frequency that can be detected from
departure from Hardy-Weinberg and linkage equilibrium.
Geneland requires individual multilocus genetic data that are optionally geo-referenced.
It implements several models that can make use of both geographic
and genetic informations to estimate the number of populations in a dataset and
delineate their spatial organisation.
Important areas of application include landscape genetics, conservation genetics, human genetics, anthropology and epidemiology.
Geneland can handle all common types of co-dominant or dominant markers
(microsatellites, SNPs, AFLP, sequence data).
Since version 4.0.0, the program can also process phenotypic data and therefore any combination of genetic, phenotypic and geographic
information.
The program is released as an add-on to the free statistical program R and is currently available for Linux,
Mac-OS and Windows.
It includes a
fully clickable user interface requiring no particular knowledge of R.
G. Guillot, S. Renaud, R. Ledevin, J. Michaux, J. Claude
A Unifying Model for the Analysis of Phenotypic, Genetic and Geographic Data.
Systematic Biology, 61(5) 897-911, 2012.
[pdf] [SM] [Syst. Biol.]
B. Guedj and G. Guillot
Estimating the location and shape of hybrid zones
Molecular Ecology Resources 11(6), 1119-1123, 2011.
[preprint]
G. Guillot and F. Santos
A computer program to simulate multilocus genotype data with spatially
auto-correlated allele frequencies. Molecular Ecology Resources,
9(4), 1112-1120, 2009.
[preprint] [Supplementary material]
G. Guillot.
Inference of structure in subdivided populations at low levels of genetic
differentiation. The correlated allele frequencies model revisited. Bioinformatics,
24:2222-2228, 2008.
[preprint] [Supplementary material]
G. Guillot, F. Santos and A. Estoup.
Analysing georeferenced population genetics data with Geneland:
a new algorithm to deal with null alleles and a
friendly graphical user interface. Bioinformatics, 24(11):1406-1407, 2008.
[preprint][Supplementary material]
G. Guillot, Mortier, F., Estoup, A.
Geneland: A program for landscape genetics. Molecular Ecology Notes, 5, 712-715, 2005.
G. Guillot, Estoup, A., Mortier, F. Cosson, J.F.
A spatial statistical model for landscape genetics. Genetics, 170, 1261-1280, 2005.
[preprint]
Guillot G. and F. Rousset
Dismantling the Mantel tests. To appear in Methods in Ecology and Evolution.
[pdf]
Blair C, Weigel DE, Balazik M, Keeley AT, Walker FM, Landguth E, Cushman S, Murphy M, Waits L, Balkenhol N..
A simulation-based evaluation of methods for inferring linear barriers to gene flow, Mol. Ecol. Resour. 2012
[MER]
Remais J.V., Xiao N., Akullian A., Qiu D., Blair D.
Genetic Assignment Methods for Gaining Insight into the Management of
Infectious Disease by Understanding Pathogen, Vector, and Host Movement.
PLoS Pathogens 7(4): e1002013.
[PLoS Pathogens]
G. Guillot, R. Leblois, A. Coulon, A. Frantz
Statistical methods in spatial genetics. Molecular Ecology, to appear.
[preprint][Supplementary material]
G. Guillot
On the inference of spatial structure from population genetics data using the Tess program.
Bioinformatics 2009.
[preprint] [Supplementary material]
M. Hansen and J. Hemmer-Hansen Landscape genetics goes to sea. Journal of Biology 6:6 2007.
[J. Biol. web site]
L. Excoffier and G. Heckel
Computer programs for population genetics data analysis: a survival guide.
Nature Reviews Genetics 7, 745-758, October 2006.
[pdf]
Rieux A.,
T. Lenormand, J. Carlier, L. de Lapeyre de Bellair, V. Ravigné
Using neutral cline decay to estimate contemporary
dispersal: a generic tool and its application to a major
crop pathogen 2013
[Ecology Letters]
M. Delętre, McKey D.B., Hodkinson T.R.
Marriage exchanges, seed exchanges, and the dynamics of manioc diversity.
PNAS 2011 108 (45) 18249-18254;
[PNAS]
Macholán M, Baird SJ, Dufková P, Munclinger P, Bímová BV, Piálek J.
Assessing multilocus introgression patterns: a case study on the mouse X chromosome in central Europe. Evolution, 65(5), 1428-1446, 2011.
[Evolution]
Beadell, JS; Hyseni, C; Abila, PP;
Azabo, R; Enyaru, JCK; Ouma, JO; Mohammed, YO; Okedi, LM; Aksoy, S; Caccone, A.
Phylogeography and Population Structure of Glossina fuscipes
fuscipes in Uganda: Implications for Control of Tsetse, PLoS Neglected Tropical Diseases web site, 2010
[PLoS Neglected Tropical Diseases web site]
J. A. Galarza, J. Carreras-Carbonell,
E.Macpherson, M.Pascual, S. Roques, G.F. Turner and C. Ricod . The influence of oceanographic fronts and early-life-history traits
on connectivity among littoral fish species. PNAS, 106(5), 1473-1478, 2009.
[PNAS web site]
L. Joseph, G. Dolman, S. donnellan, K. M. Saint,
M. L. Berg, A.T. Bennet. Where and when does a ring start and end? Testing the ring-species hypothesis
in a species complex of Australian parrots. Proc. Roy. Soc. B, 275: 2431-2440, 2008.
[Proc. B web site]
Coulon A., Fitzpatrick J.W., Bowman R., Stith B.M.,
Makarewich C.A., Stenzler L.M. and Lovette I.J.
Congruent population structure inferred from dispersal behaviour and
intensive genetic surveys of the threatened Florida Scrub-Jay
(Aphelocoma coerulescens). Molecular Ecology, 17 1685-1701, 2008. [Mol. Ecol. web site][News and views]
U. Hannelius, E. Salmela,
T. Lappalainen, G. Guillot, C.M. Lindgren, U. von
Döbeln, P. Lahermo, P. and J. Kere. Population
substructure in Finland and Sweden revealed by a small number of
unlinked autosomal SNPs. BMC Genetics, 9:54, 2008.
[BMC Genetics]
B.N.Sacks, D.L. Bannasch, B.B. Chomel and H.B. Ernest
Coyotes Demonstrate How Habitat Specialization by Individuals of a Generalist Generalist Species Can Diversify Populations in a Heterogeneous
Ecoregion. Molecular Biology and Evolution 25(7):1384-1394, 2008.
[Mol. Biol. Evol. web site]
M. Fontaine, S. Baird, et al.
Rise of oceanographic barriers in continuous populations of a cetacean:
the genetic structure of harbour porpoises in Old World waters.
BMC Biology, 2007.doi:10.1186/1741-7007-5-30
[pdf]
A. Coulon, G. Guillot
G., Cosson J.-F., Angibault J.M.A. Aulagnier S.,
Cargnelutti B., Galan M., Hewison A.J.M.
Genetic structure is influenced by lansdcape features. Empirical evidence from a roe deer
population. Molecular Ecology, 15 1669-1679, 2006.
[preprint]
Courses/seminars on the Geneland program, statistical methods in landscape/spatial genetics
and applications have been organized earlier in many places worldwide.
Groups interested in organizing such a course are welcome to
contact Gilles Guillot to discuss possible options.