Selected article for: "differential expression and discovery rate"
Author: Marriott, Andrew S.; Vasieva, Olga; Fang, Yongxiang; Copeland, Nikki A.; McLennan, Alexander G.; Jones, Nigel J.
Title: NUDT2 Disruption Elevates Diadenosine Tetraphosphate (Ap(4)A) and Down-Regulates Immune Response and Cancer Promotion Genes
  • Document date: 2016_5_4
    • ID: 0ozzbp85_12
    Snippet: used produced a second-strand library type (R1 is expected to map on the 5 0 !3 0 strand and R2 on the 3 0 !5 0 strand). Reads aligning to the reference in more than one position were discarded and FKPM values (fragments per kilobase transcript per million reads mapped) calculated. Differential gene expression analysis was conducted in the R environment using the edgeR package [42] . The count data were normalised across libraries using the Trimm.....
    Document: used produced a second-strand library type (R1 is expected to map on the 5 0 !3 0 strand and R2 on the 3 0 !5 0 strand). Reads aligning to the reference in more than one position were discarded and FKPM values (fragments per kilobase transcript per million reads mapped) calculated. Differential gene expression analysis was conducted in the R environment using the edgeR package [42] . The count data were normalised across libraries using the Trimmed Mean M-values (TMM) method in edgeR with default parameters. Tagwise dispersion parameters were estimated and then used for log 2 FC (log 2 Fold Change) estimation and testing in edgeR using the Likelihood Ratio (LR test) [43] . P values associated with log 2 FC were adjusted for multiple testing using the False Discovery Rate (FDR) approach [44] . Significant DEGs were defined as those with an FDR-adjusted P value < 0.05. All original RNA-Seq data produced in this study have been submitted to the EMBL-EBI ArrayExpress database under accession number E-MTAB-4104.

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