Author Archives: Edmond Sanou

Four network graphs of the same shape (x1 connected to x2 and x3, x2 and x3 also connected to x4, and x4 also connected to x5) with different node colors labelled i, ii, iii, iv. There is a legend with a a peach node labelled A, first set, a yellow node labelled B, second set, and a blue node labelled C, separating set with the text Conditional independence properties A independent symbol B | C. In i x1 is peach, x2 and x3 are blue and x4 and x5 are yellow, in ii x2 is peach, x1 and x4 are blue, and x3, x5 are yellow, in iii x1, x2, and x3 are peach, x4 is blue, and x5 is yellow, and in iv x1 is peach, x2 and x3 are plain, and x5 is yellow
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Article: Gaussian graphical models with applications to omics analysesAuthors and Year: Katherine H. Shutta, Roberta De Vito, Denise M. Scholtens, Raji Balasubramanian 2022Journal: Statistics in Medicine Review Prepared by: Sanou Edmond, Postdoc in BiostatisticsNuclear Safety and Radiation Protection Authority (ASNR) As scientists collect more detailed biological data, they use networks to understand how molecules in the body interact and how these interactions relate to disease. This type of data, known as omics, includes information about genes (genomics), proteins (proteomics), and other molecules. These networks can help find genes linked to illness and even suggest possible treatment options. Statisticians help by using tools that highlight which molecules are directly connected. In their tutorial “Gaussian Graphical Models with Applications to Omics Analyses,” Shutta et al. recommend using a method called Gaussian Graphical Models (GGMs) to study these connections. GGMs help draw simple, clear maps of how molecules relate to each other. The authors…

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