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Additional file 4 of Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

Authors :
Seyres, Denis
Cabassi, Alessandra
Lambourne, John J.
Burden, Frances
Farrow, Samantha
McKinney, Harriet
Batista, Joana
Kempster, Carly
Pietzner, Maik
Slingsby, Oliver
Cao, Thong Huy
Quinn, Paulene A.
Stefanucci, Luca
Sims, Matthew C.
Rehnstrom, Karola
Adams, Claire L.
Frary, Amy
Erg��ener, Bekir
Kreuzhuber, Roman
Mocciaro, Gabriele
D���Amore, Simona
Koulman, Albert
Grassi, Luigi
Griffin, Julian L.
Ng, Leong Loke
Park, Adrian
Savage, David B.
Langenberg, Claudia
Bock, Christoph
Downes, Kate
Wareham, Nicholas J.
Allison, Michael
Vacca, Michele
Kirk, Paul D. W.
Frontini, Mattia
Publication Year :
2022
Publisher :
figshare, 2022.

Abstract

Additional file 4: Fig. S4. Related to Figure 3���Multi-omic signatures of extreme phenotype groups and their use in prediction. A. Plots showing individuals ranked by their predicted probability of belonging to the obese group. As in Figure 3C, but for the Methylation (monocytes), RNA-Seq (monocytes), Metabolites, and ChIP-Seq (monocytes) data layers. B. Multi-omic model trained using lipodystrophy patients often predicts obese individuals to belong to the lipodystrophy group. As in Figure 3C (final plot), but training the multi-layer model using the Lipodystrophy and Lean-BD groups (rather than the Obese and Lean-BD groups). Using this model, Obese individuals were often predicted as belonging to the Lipodystrophy group.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....a25f62e38c216dc95c413e7a9ca4c383
Full Text :
https://doi.org/10.6084/m9.figshare.19351224