Selected article for: "absolute log and false discovery rate"
Author: Josset, Laurence; Zeng, Hui; Kelly, Sara M.; Tumpey, Terrence M.; Katze, Michael G.
Title: Transcriptomic Characterization of the Novel Avian-Origin Influenza A (H7N9) Virus: Specific Host Response and Responses Intermediate between Avian (H5N1 and H7N7) and Human (H3N2) Viruses and Implications for Treatment Options
  • Document date: 2014_2_4
    • ID: uz0m1o0q_27
    Snippet: Statistical analysis. Differential expression was determined by comparing IAV-infected replicates to time-matched mocks, based on a linear model fit for each probe using the R software package "limma" (42) . Criteria for differential expression were an absolute log 2 FC of 1.5 and a q value of Ͻ0.01 calculated using a moderated t test with subsequent Benjamini-Hochberg correction. This controls the false discovery rate (FDR) associated with our .....
    Document: Statistical analysis. Differential expression was determined by comparing IAV-infected replicates to time-matched mocks, based on a linear model fit for each probe using the R software package "limma" (42) . Criteria for differential expression were an absolute log 2 FC of 1.5 and a q value of Ͻ0.01 calculated using a moderated t test with subsequent Benjamini-Hochberg correction. This controls the false discovery rate (FDR) associated with our results to 1%. For each viral condition, genes were classified as up-or downregulated throughout infection if they were found significantly up-or downregulated at at least one time point. Genes that were found to be both up-and downregulated at different time points were classified as genes with transient expression. A binary DE matrix with 3 columns per viral treatment (gene up-or downregulated or transient genes) and values equal to 1 for DE and 0 for not DE was used to cluster DE genes in 25 clusters by Euclidian distance and constant height cut of a hierarchical clustering dendrogram (43) .

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