The result of a differential expression analysis done between napabucasin treated and DMSO control parental MiaPaCa2 cells. The cells were treated for 2 hours with 0.5 uM napabucasin. The protocol to generate the RNA-seq is described in Froeling F.E.M. et al 2019.

Source: R/enrichViewNet.R

The object is a data.frame with 24184 rows and 4 columns. Each row correspond to a tested gene.

data(parentalNapaVsDMSODEG)

Format

a data.frame containing the results of a differential expression analysis between napabucasin treated and DMSO control parental MiaPaCa2 cells for all 24184 genes tested. The 4 columns are:

  • "EnsemblID": a character string representing the unique Ensembl identifier for the tested gene

  • "log2FoldChange": a numeric representing the expression difference (in log2FoldChange) between the napabucasin treatment and the DMSO control for the tested gene

  • "padj": a numeric representing the adjusted p-value associated to the difference in expression for the tested gene

  • "GeneName": a character string representing the name of the tested gene

Source

The original RNA-sequencing data is available at the Gene Expression Omnibus (GEO) under the accession number GSE135352.

Value

a data.frame containing the results of a differential expression analysis between napabucasin treated and DMSO control parental MiaPaCa2 cells for all 24184 genes tested. The 4 columns are:

  • "EnsemblID": a character string representing the unique Ensembl identifier for the tested gene

  • "log2FoldChange": a numeric representing the expression difference (in log2FoldChange) between the napabucasin treatment and the DMSO control for the tested gene

  • "padj": a numeric representing the adjusted p-value associated to the difference in expression for the tested gene

  • "GeneName": a character string representing the name of the tested gene

Details

The differentially expressed genes between napabucasin-treated cells (0.5 uM) and DMSO as vehicle control are reprinted from Clinical Cancer Research, 2019, 25 (23), 7162–7174, Fieke E.M. Froeling, Manojit Mosur Swamynathan, Astrid Deschênes, Iok In Christine Chio, Erin Brosnan, Melissa A. Yao, Priya Alagesan, Matthew Lucito, Juying Li, An-Yun Chang, Lloyd C. Trotman, Pascal Belleau, Youngkyu Park, Harry A. Rogoff, James D. Watson, David A. Tuveson, Bioactivation of napabucasin triggers reactive oxygen species–mediated cancer cell death, with permission from AACR.

See also

  • createNetwork for transforming functional enrichment results from gprofiler2 into a Cytoscape network

  • createEnrichMap for transforming functional enrichment results from gprofiler2 into an enrichment map

Examples


## Required library
library(gprofiler2)

## Loading data set containing the results of a differentially expressed 
## analysis between 2-hour treatment with 0.5 uM napabucasin and 
## DMSO vehicle control parental MiaPaCa2 cells
data(parentalNapaVsDMSODEG)

allGenes <- unique(parentalNapaVsDMSODEG$EnsemblID)

## Select the significantly differentially expressed genes
selection <- which(abs(parentalNapaVsDMSODEG$log2FoldChange) > 1 & 
                            parentalNapaVsDMSODEG$padj < 0.05)
                            
selectedGenes <- unique(parentalNapaVsDMSODEG$EnsemblID[selection])

## Run an enrichment analysis using WikiPathways dataset
gostres <- gost(query = list(parental_napa_vs_DMSO=selectedGenes),
    organism="hsapiens",
    correction_method = "g_SCS",
    sources=c("WP"), significant=TRUE, evcodes=TRUE,
    custom_bg=allGenes, exclude_iea=TRUE)
#> Detected custom background input, domain scope is set to 'custom'.