The enormous amount of genetic and genomic data generated in the last decade shows great promise in our ability to understand better human diseases and improving public health. Yet, the genetic architecture of complex human phenotypes remains elusive, and important questions are still unanswered. Our research addresses methodological issues related to the analysis of large multidimensional data in genetics and genomics. It focuses on particular on the development and application of innovative methods that aim at i) improving association mapping in large genomics datasets where multiple correlated variables are measured across multiple biological levels; ii) allowing for the robust evaluation of causal models that include both genetic, genomic, clinical and environmental data; and iii) identifying and targeting discoveries that have the highest potential clinical utility. We have developed several packages for the analysis of genetic data in human. Most of them are available here: https://gitlab.pasteur.fr/statistical-genetics
Click to view graph
Connections
Members
Former Members
2000
2000
Name
Position
2019
2020
Fabien Laporte
Postdoc
2017
2020
Vincent Laville
Postdoc
2017
2019
Amaury Vaysse
Postdoc
2016
2018
Florian Privé
PhD Student
2021
2022
Lucie Troubat
Research Engineer
2017
2018
Apolline Gallois
Research Engineer
2016
2017
Vincent Guillemot
Research Engineer
2020
2020
Sayeh Kazem
Undergraduate Student
2020
2020
Daniel Rodriguez-Pinzon
Undergraduate Student
2020
2020
Gabriel Pires
Undergraduate Student
2019
2019
Chunzi Yao
Undergraduate Student
2019
2019
Raouf Boukenna
Undergraduate Student
2017
2017
Carla Lasry
Undergraduate Student
2022
2022
Violeta Basten Romero
Undergraduate Student
2023
2023
Meryem Memmadi
Undergraduate Student
2023
2023
Xiang Li
PhD Student
2023
2023
Deniz Fettahoglu
Undergraduate Student
2023
2023
Anja Estermann
Undergraduate Student