Selected article for: "enrichment analysis and fold change"
Author: Geng, Lingling; Liu, Zunpeng; Zhang, Weiqi; Li, Wei; Wu, Zeming; Wang, Wei; Ren, Ruotong; Su, Yao; Wang, Peichang; Sun, Liang; Ju, Zhenyu; Chan, Piu; Song, Moshi; Qu, Jing; Liu, Guang-Hui
Title: Chemical screen identifies a geroprotective role of quercetin in premature aging
  • Document date: 2018_8_1
    • ID: 1mrj6nb3_72
    Snippet: The pipeline of RNA-seq data processing has been described previously . In brief, sequencing reads were trimmed and mapped to hg19 human genome using hisat2 software (v2.0.4) (Kim et al., 2015) . The transcriptional expression level of each gene was counted by HTSeq (v0.6.1) (Anders et al., 2015) . Differentially expressed genes (DEGs) were computed using DESeq2 at a cutoff adjust P value (Benjamini-Hochberg) less than 0.05 and |Log 1.5 (fold cha.....
    Document: The pipeline of RNA-seq data processing has been described previously . In brief, sequencing reads were trimmed and mapped to hg19 human genome using hisat2 software (v2.0.4) (Kim et al., 2015) . The transcriptional expression level of each gene was counted by HTSeq (v0.6.1) (Anders et al., 2015) . Differentially expressed genes (DEGs) were computed using DESeq2 at a cutoff adjust P value (Benjamini-Hochberg) less than 0.05 and |Log 1.5 (fold change)| more than 1 (Love et al., 2014) . The correlation between replicates of each sample was evaluated by the Pearson correlation coefficient (R), which was based on DESeq2 regularized-logarithm (rlog) normalized read count. Gene Ontology (GO) and pathway enrichment analysis was conducted by ToppGene (Chen et al., 2009 ). Protein-protein interaction networks of differentially expressed genes was drawn based on the STRING database (Szklarczyk et al., 2017) .

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