Gilles Guillot

Summary

Affiliation: University of Oslo
Country: Norway

Publications

  1. ncbi Population substructure in Finland and Sweden revealed by the use of spatial coordinates and a small number of unlinked autosomal SNPs
    Ulf Hannelius
    Department of Biosciences and Nutrition, Karolinska Institutet, 14157 Huddinge, Sweden
    BMC Genet 9:54. 2008
  2. ncbi Analysing georeferenced population genetics data with Geneland: a new algorithm to deal with null alleles and a friendly graphical user interface
    Gilles Guillot
    Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P O Box 1066 Blindern, 0316 Oslo, Norway
    Bioinformatics 24:1406-7. 2008
  3. ncbi Inference of structure in subdivided populations at low levels of genetic differentiation--the correlated allele frequencies model revisited
    Gilles Guillot
    Department of Biology, Centre for Ecological and Evolutionary Synthesis, University of Oslo, P O Box 1066 Blindern, 0316 Oslo, Norway
    Bioinformatics 24:2222-8. 2008
  4. ncbi Correcting for ascertainment bias in the inference of population structure
    Gilles Guillot
    Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P O Box 1066, Blindern 0316, Oslo, Norway
    Bioinformatics 25:552-4. 2009
  5. ncbi On the inference of spatial structure from population genetics data
    Gilles Guillot
    Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P O Box 1066, Blindern 0316, Oslo Norway
    Bioinformatics 25:1796-801. 2009
  6. ncbi A spatial statistical model for landscape genetics
    Gilles Guillot
    Unité de Mathématiques et Informatique Appliquées, INRA INAPG ENGREF, Paris, France 75231
    Genetics 170:1261-80. 2005
  7. ncbi Bayesian clustering using hidden Markov random fields in spatial population genetics
    Olivier Francois
    TIMC, TIMB Department of Mathematical Biology, La Tronche, France
    Genetics 174:805-16. 2006
  8. ncbi Discrimination and scoring using small sets of genes for two-sample microarray data
    Gilles Guillot
    INRA, Applied Mathematics Department, Paris, France
    Math Biosci 205:195-203. 2007

Detail Information

Publications8

  1. ncbi Population substructure in Finland and Sweden revealed by the use of spatial coordinates and a small number of unlinked autosomal SNPs
    Ulf Hannelius
    Department of Biosciences and Nutrition, Karolinska Institutet, 14157 Huddinge, Sweden
    BMC Genet 9:54. 2008
    ..However, some studies have suggested that this number could be reduced if the individual spatial coordinates are taken into account in the analysis...
  2. ncbi Analysing georeferenced population genetics data with Geneland: a new algorithm to deal with null alleles and a friendly graphical user interface
    Gilles Guillot
    Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P O Box 1066 Blindern, 0316 Oslo, Norway
    Bioinformatics 24:1406-7. 2008
    ..It now includes a fully clickable graphical interface. Informations on how to get the software are available on folk.uio.no/gillesg/Geneland.html..
  3. ncbi Inference of structure in subdivided populations at low levels of genetic differentiation--the correlated allele frequencies model revisited
    Gilles Guillot
    Department of Biology, Centre for Ecological and Evolutionary Synthesis, University of Oslo, P O Box 1066 Blindern, 0316 Oslo, Norway
    Bioinformatics 24:2222-8. 2008
    ..Under this model, various problems of inference are considered, in particular the common and difficult, but still unaddressed, situation where the number of populations is unknown...
  4. ncbi Correcting for ascertainment bias in the inference of population structure
    Gilles Guillot
    Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P O Box 1066, Blindern 0316, Oslo, Norway
    Bioinformatics 25:552-4. 2009
    ..Attempting to model this censoring process in view of making inference of population structure (i.e.identifying clusters of individuals) brings up challenging numerical difficulties...
  5. ncbi On the inference of spatial structure from population genetics data
    Gilles Guillot
    Centre for Ecological and Evolutionary Synthesis, Department of Biology, University of Oslo, P O Box 1066, Blindern 0316, Oslo Norway
    Bioinformatics 25:1796-801. 2009
    ..Arabidopsis thaliana data previously analysed with this method are also reconsidered...
  6. ncbi A spatial statistical model for landscape genetics
    Gilles Guillot
    Unité de Mathématiques et Informatique Appliquées, INRA INAPG ENGREF, Paris, France 75231
    Genetics 170:1261-80. 2005
    ..g., FST<0.05). The method is then applied to a set of 88 individuals of wolverines (Gulo gulo) sampled in the northwestern United States and genotyped at 10 microsatellites...
  7. ncbi Bayesian clustering using hidden Markov random fields in spatial population genetics
    Olivier Francois
    TIMC, TIMB Department of Mathematical Biology, La Tronche, France
    Genetics 174:805-16. 2006
    ..We illustrate and discuss the implementation issues with the Scandinavian brown bear and the human CEPH diversity panel data set...
  8. ncbi Discrimination and scoring using small sets of genes for two-sample microarray data
    Gilles Guillot
    INRA, Applied Mathematics Department, Paris, France
    Math Biosci 205:195-203. 2007
    ..The computer code that we developed to make computations is available as an R package...