UMR CNRS 5558 Laboratoire de Biométrie et Biologie Évolutive

• Activities
  • +PhD work -PhD work

    My PhD work is to examin the role multidimensional methods can play in genetic data analysis. Ordination methods offer great opportunities to explore molecular marker data.

    Presently, I have devoted attention to two particular points. First, a problem arises when trying to find typology of individuals or populations using molecular markers : each marker can perform its own typology. Thus, it seems important to be able to find and compare the informations provided by each marker, and if possible, to find a compromise between these informations. On a statistical point of view, this question can be tackled in the K-tables ordination methods framework. A first appilcation using the Multiple Co-inertia Analysis (MCOA) allowed to propose a possible measure of the typological value of molecular markers (Jombart et al 2006, Laloë et al, accepted).

    Another point concerns the research of spatial structures in the genetic variability. When available, spatial information can be used along with genetic distances to infer underlying biological processes. This can be achieved using spatially constrained (or also ’spatially explicit’) ordination methods. In this context, I propose the spatial Principal Component Analysis (sPCA, Jombart et al, in prep). This method, although new in genetics, relies on a well-known ordination method (Principal Component Analysis on allelic frequency data) and of spatial autocorrelation.

    These two questions are tackled through the analysis of genetic datasets, involving several collaborations. This interdisciplinary dialogue required software development, now regrouped in the adegenet package (http://pbil.univ-lyon1.fr/software/adegenet/) du lfor the free software R. This package is devoted to genetic data handling, starting from data import from foreign softwares (e.g. GENETICS, Fstat) to their analysis using reduced space ordinations available in the ade4 package. Other common functionalities are also proposed (HW tests, hierarchical structuration tests, …) as well as data export to other R packages (hierfstat, genetics, …). I also contribute to the ade4 package.

  • +Information -Information

    You will find more information on my homepage.

+Publications -Publications