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

High-dimensional and statistical learning

Automatic analysis of cell populations

New publication:

Hejblum BP, Alkhassim C, Gottardo R, Caron F, Thiébaut R, Sequential Dirichlet process mixture of skew t-distributions for model-based clustering of flow cytometry data, Annals of Applied Statistics, 13(1):638-660, 2019. DOI: 10.1214/18-AOAS1209.

High-dimensional compositional data analysis

Perrine Soret (PhD student in the axis "High-dimensional and statistical learning", supervised by M. Avalos) has applied our expertise in high dimensional data analysis to human microbiome field of research:

Soret P, Vandenborght LE, Francis F, Coron N, Enaud R, The Mucofong Investigation Group, Avalos M, Schaeverbeke T, Berger P, Fayon M, Thiébaut R and Delhaes L. Respiratory mycobiome and suggestion of inter-kingdom network during acute pulmonary exacerbation in cystic fibrosis. To appear in Scientific Reports.

Missing Value Treatment in Longitudinal High Dimensional Supervised Problems

Poor blood sample quality introduces a large number of missing values in the context of sequencing data production. Furthermore, strong technical biases may force the analyst to remove the considered sequenced samples. Then entire day dependent data are then missing. Hadrien Lorenzo (PhD student in the axis "High-dimensional and statistical learning", supervised by J. Saracco and R. Thiébaut) has developed a multi-block approach: the dd-sPLS method. dd-sPLS has been applied to high dimensional data analysis of different fields of research:

Lorenzo, H., Misbah, R., Odeber, J., Morange, P. E., Saracco, J., Trégouët, D. A., and Thiébaut, R. High-dimensional multi-block analysis of factors associated with thrombin generation potential. In 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS) (pp. 453-458). IEEE.

Ellies-Oury, M. P., Lorenzo, H., Denoyelle, C., Saracco, J., and Picard, B. An Original Methodology for the Selection of Biomarkers of Tenderness in Five Different Muscles. Foods, 8(6), 206 (2019).