Overall Objectives
Research Program
Application Domains
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
XML PDF e-pub
PDF e-Pub

Section: New Results

Statistical analysis of genomic data

Participants : Gilles Celeux, Christine Keribin, Yann Vasseur, Kevin Bleakley.

The subject of Yann Vasseur's PhD Thesis, supervised by Gilles Celeux and Marie-Laure Martin-Magniette (INRA URGV), was the inference of a regulatory network for Transcriptions Factors (TFs), which are specific genes, of Arabidopsis thaliana. For this, a transcriptome dataset with a similar number of TFs and statistical units was available. They reduced the dimension of the network to avoid high-dimensional difficulties. Representing this network with a Gaussian graphical model, the following procedure was defined:

  1. Selection step: choose the set of TF regulators (supports) of each TF.

  2. Classification step: deduce co-factor groups (TFs with similar expression levels) from these supports.

Thus, the reduced network would be built on the co-factor groups. Currently, several selection methods based on Gauss-LASSO and resampling procedures have been applied to the dataset. The study of stability and parameter calibration of these methods is in progress. The TFs are clustered with the Latent Block Model into a number of co-factor groups, selected with BIC or the exact ICL criterion. Since these models are built in an ad hoc way, Yann Vasseur has defined complex simulation tools to asses their performances in a proper way.

In collaboration with Benno Schwikowski, Iryna Nikolayeva and Anavaj Sakuntabhai (Pasteur Institute, Paris), Kevin Bleakley worked on using 2-d isotonic regression to predict dengue fever severity at hospital arrival using high-dimensional microarray gene expression data. Important marker genes for dengue severity have been detected, some of which now have been validated in external lab trials, and an article has now been submitted.

In collaboration with researchers from the Pasteur Institute, Kevin Bleakley worked on statistical tests in the context of research into what leads to dengue fever without symptoms as opposed to with symptoms. This work was published in Science Translational Medicine.

Kevin Bleakley has also collaborated with Inserm/Paris-Saclay researchers at Kremlin-BicĂȘtre hospital on cyclic transcriptional clocks and renal corticosteroid signaling, and has developed novel statistical tests for detecting synchronous signals. This work is submitted.