Selected article for: "Benjamini Hochberg negative log and correlation structure"
Author: Nathalie Pamir; Calvin Pan; Deanna L. Plubell; Patrick M. Hutchins; Chongren Tang; Jake Wimberger; Angela Irwin; Thomas Q. de Aguiar Vallim; Jay W. Heinecke; Aldons J. Lusis
Title: Genetic control of the HDL proteome
  • Document date: 2018_8_31
    • ID: hx7n4xfo_34
    Snippet: Jay Heinecke is named as a co-inventor on patents from the US Patent Office on the use of HDL markers to predict the risk of cardiovascular disease. Dr. Heinecke has served as a consultant for Kowa, Merck, Amgen, Bristol Meyer Squibb, GSK, and Pacific Biomarkers. . Hierarchical clustering of the HDL metrics: Proteome, sterol efflux, particle concentration and size. min.MF, plus.MF, delta.BHK are unstimulated, ABCA1 upregulated and ABCA1 specific .....
    Document: Jay Heinecke is named as a co-inventor on patents from the US Patent Office on the use of HDL markers to predict the risk of cardiovascular disease. Dr. Heinecke has served as a consultant for Kowa, Merck, Amgen, Bristol Meyer Squibb, GSK, and Pacific Biomarkers. . Hierarchical clustering of the HDL metrics: Proteome, sterol efflux, particle concentration and size. min.MF, plus.MF, delta.BHK are unstimulated, ABCA1 upregulated and ABCA1 specific sterol efflux from BHK cells respectively. min.cAMP, plus.cAMP, delta.J774 are unstimulated, ABCA1 upregulated and ABCA1 specific sterol efflux from J774 cells respectively. m.hdl.size and l.hdl.size are medium and large HDL sizes respectively. The correlation structure was determined using pearson correlation. The protein functional groups were curated from DAVID, KEGG, Panther, and Uniprot databases. Figure 1 . Self-loops were removed and edges were bundled for clarity. Node locations are assigned using an edge-weighted spring-embedded layout algorithm using the negative log of the Benjamini-Hochberg corrected p-value, and edge transparency is directly proportional to the same value. Red: negative correlation, Blue: positive correlation. Shorter distances indicate stronger correlations.

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