rosaNapaVsDMSODEG: The result of a differential expression analysis done between...

rosaNapaVsDMSODEGR Documentation

The result of a differential expression analysis done between napabucasin treated and DMSO control MiaPaCa2 cells stably expressing the Rosa26 control vector. 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.

Description

The object is a data.frame with 23542 rows and 4 columns. Each row correspond to a tested gene.

Usage

data(rosaNapaVsDMSODEG)

Format

a data.frame containing the results of a differential expression analysis between napabucasin treated and DMSO control MiaPaCa2 cells stably expressing the Rosa26 control vector for all 23542 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.

Value

a data.frame containing the results of a differential expression analysis between napabucasin treated and DMSO control MiaPaCa2 cells stably expressing the Rosa26 control vector for all 23542 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.

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 dataset containing the results of a differentially expressed 
## analysis between 2-hour treatment with 0.5 uM napabucasin and 
## DMSO vehicle control MiaPaCa2 cells stably expressing the 
## Rosa26 control vector
data(rosaNapaVsDMSODEG)

allGenes <- unique(rosaNapaVsDMSODEG$EnsemblID)

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

## Run an enrichment analysis using Transfac dataset (transcription factor)
gostres <- gost(query = list(rosa_napa_vs_DMSO=selectedGenes),
    organism="hsapiens",
    correction_method = "g_SCS",
    sources=c("TF"), significant=TRUE, evcodes=TRUE,
    custom_bg=allGenes, exclude_iea=TRUE)




adeschen/gprofiler2cytoscape documentation built on April 26, 2024, 9:33 p.m.