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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()
)