Selected article for: "gene expression and geometric mean"
Author: Jorge Blazquez-Prieto; Covadonga Huidobro; Ines Lopez-Alonso; Laura Amado-Rodriguez; Paula Martin-Vicente; Cecilia Lopez-Martinez; Irene Crespo; Cristina Pantoja; Pablo J Fernandez-Marcos; Manuel Serrano; Jacob I Sznajder; Guillermo M Albaiceta
Title: Cellular senescence limits acute lung injury induced by mechanical ventilation
  • Document date: 2020_3_25
    • ID: ebwxryai_8
    Snippet: Normalized datasets were pooled using the Combat-Co-normalization using controls (COCONUT) algorithm (14) . This method normalizes gene expression of the different datasets using an empirical Bayes fitting, but applied only to control samples (in this case, spontaneously breathing animals with intact lungs). Then the obtained normalization parameters are applied to the cases (i.e., those with lung injury)(Supplementary Figure 1) . A senescence me.....
    Document: Normalized datasets were pooled using the Combat-Co-normalization using controls (COCONUT) algorithm (14) . This method normalizes gene expression of the different datasets using an empirical Bayes fitting, but applied only to control samples (in this case, spontaneously breathing animals with intact lungs). Then the obtained normalization parameters are applied to the cases (i.e., those with lung injury)(Supplementary Figure 1) . A senescence meta-score was computed for each sample as the geometric mean of the upregulated genes minus the geometric mean of the downregulated genes in the senescence signature. Meta-scores were finally compared among controls and animals with lung injury and/or mechanical ventilation.

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