R: Differential gene expression analysis results

diff_express {ggpubr} | R Documentation

## Differential gene expression analysis results

### Description

Differential gene expression analysis results obtained from comparing the RNAseq data of two different cell populations using DESeq2

### Usage

    data("diff_express")

### Format

A data frame with 36028 rows and 5 columns.

`name`

  gene names

`baseMean`

  mean expression signal across all samples

`log2FoldChange`

  log2 fold change

`padj`

  Adjusted p-value

`detection_call`

  a numeric vector specifying whether the genes is expressed (value = 1) or not (value = 0).

### Examples

    data(diff_express)

    # Default plot
    ggmaplot(diff_express, main = expression("Group 1" %->% "Group 2"),
       fdr = 0.05, fc = 2, size = 0.4,
       palette = c("#B31B21", "#1465AC", "darkgray"),
       genenames = as.vector(diff_express$name),
       legend = "top", top = 20,
       font.label = c("bold", 11),
       font.legend = "bold",
       font.main = "bold",
       ggtheme = ggplot2::theme_minimal())

    # Add rectangle around labesl
    ggmaplot(diff_express, main = expression("Group 1" %->% "Group 2"),
       fdr = 0.05, fc = 2, size = 0.4,
       palette = c("#B31B21", "#1465AC", "darkgray"),
       genenames = as.vector(diff_express$name),
       legend = "top", top = 20,
       font.label = c("bold", 11), label.rectangle = TRUE,
       font.legend = "bold",
       font.main = "bold",
       ggtheme = ggplot2::theme_minimal())

[Package ggpubr version 0.1.6 Index]