High-Dimensional Multi-Block Analysis of Factors Associated with Thrombin Generation Potential
RAZZAQ, Misbah
Université de Bordeaux [UB]
Institut National de la Santé et de la Recherche Médicale [INSERM]
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Université de Bordeaux [UB]
Institut National de la Santé et de la Recherche Médicale [INSERM]
RAZZAQ, Misbah
Université de Bordeaux [UB]
Institut National de la Santé et de la Recherche Médicale [INSERM]
Université de Bordeaux [UB]
Institut National de la Santé et de la Recherche Médicale [INSERM]
SARACCO, Jérôme
Quality control and dynamic reliability [CQFD]
Institut de Mathématiques de Bordeaux [IMB]
Ecole Nationale Supérieure de Cognitique [ENSC]
Quality control and dynamic reliability [CQFD]
Institut de Mathématiques de Bordeaux [IMB]
Ecole Nationale Supérieure de Cognitique [ENSC]
TRÉGOUËT, David-Alexandre
Université de Bordeaux [UB]
Institut National de la Santé et de la Recherche Médicale [INSERM]
< Reduce
Université de Bordeaux [UB]
Institut National de la Santé et de la Recherche Médicale [INSERM]
Language
en
Communication dans un congrès
This item was published in
CBMS 2019 - 32nd IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2019-06-05, Cordoba. p. 453-458
IEEE
English Abstract
The identification of novel biological factors associated with thrombin generation, a key biomarker of the coagulation process, remains a relevant strategy to disentangle pathophysiological mechanisms underlying the risk ...Read more >
The identification of novel biological factors associated with thrombin generation, a key biomarker of the coagulation process, remains a relevant strategy to disentangle pathophysiological mechanisms underlying the risk of venous thrombosis (VT). As part of the MARseille THrombosis Association Study (MARTHA), we measured whole blood DNA methylation levels, plasma levels of 300 proteins, 3 thrombin generation biomarkers (endogeneous thrombin potential, peak and lagtime), clinical and genetic data in 700 patients with VT. The application of a novel high-dimensional multi-levels statistical methodology we recently developed, the data driven sparse Partial Least Square method (ddsPLS), on the MARTHA datasets enabled us 1/ to confirm the role of a known mutation of the variability of endogenous thrombin potential and peak, 2/ to identify a new signature of 7 proteins strongly associated with lagtime.Read less <
English Keywords
Multi-Omics
High Dimensional Data
Missing Data
SVD
Partial Least Square
Variable Selection
Multi-Block Analysis
Machine Learning
Thrombine Generation
ANR Project
Medical Genomics - ANR-10-LABX-0013
Origin
Hal imported