Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

Axis 4: Linking different kinds of Omics data through a model-based clustering approach

Participants : Guillemette Marot, Vincent Vandewalle, Wilfried Heyse.

In this work, a mixture model allowing for genes clustering using both microarray (continuous) and RNAseq (count) expression data is proposed. More generally, it answers the clustering of variables issue, when variables are of different kinds (continuous and discrete here). Variables describing the same gene are constrained to belong to the same cluster. This constraint allows us to obtain a model that links the microarray and RNAseq measurements without needing parametric constraints on the form of this link. The proposed approach has been illustrated on simulated data, as well as on real data from TCGA (The Cancer Genome Atlas). It has been presented in an international conference [49].

This is a joint work with Camille Ternynck from EA2694.