MA-plot from means and log fold changes

Description

Make MA-plot which is a scatter plot of log2 fold changes (on the y-axis) versus the mean expression signal (on the x-axis).

Usage

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ggmaplot(data, fdr = 0.05, fc = 1.5, genenames = NULL,
  detection_call = NULL, size = 0.9, font.label = c(12, "plain", "black"),
  label.rectangle = FALSE, palette = c("#B31B21", "#1465AC", "darkgray"),
  top = 15, select.top.method = c("padj", "fc"), main = NULL,
  xlab = "Log2 mean expression", ylab = "Log2 fold change",
  ggtheme = theme_pubr(), ...)

Arguments

data

an object of class DESeqResults, get_diff, DE_Results, matrix or data frame containing the columns baseMean, log2FoldChange, and padj. Rows are genes.

  • baseMean: the mean expression of genes in the two groups.

  • log2FoldChange: the log2 fold changes of group 2 compared to group 1

  • padj: the adjusted p-value of the used statiscal test.

fdr

Accepted false discovery rate for considering genes as differentially expressed.

fc

the fold change threshold. Only genes with a fold change >= fc and padj <= fdr are considered as significantly differentially expressed.

genenames

a character vector of length nrow(data) specifying gene names corresponding to each row. Used for point labels.

detection_call

a numeric vector with length = nrow(data), specifying if the genes is expressed (value = 1) or not (value = 0). For example detection_call = c(1, 1, 0, 1, 0, 1). Default is NULL. If detection_call column is available in data, it will be used.

size

points size.

font.label

a vector of length 3 indicating respectively the size (e.g.: 14), the style (e.g.: "plain", "bold", "italic", "bold.italic") and the color (e.g.: "red") of point labels. For example font.label = c(14, "bold", "red").

label.rectangle

logical value. If TRUE, add rectangle underneath the text, making it easier to read.

palette

the color palette to be used for coloring or filling by groups. Allowed values include "grey" for grey color palettes; brewer palettes e.g. "RdBu", "Blues", ...; or custom color palette e.g. c("blue", "red"); and scientific journal palettes from ggsci R package, e.g.: "npg", "aaas", "lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty".

top

the number of top genes to be shown on the plot.

select.top.method

methods to be used for selecting top genes. Allowed values include "padj" and "fc" for selecting by adjusted p values or fold changes, respectively.

main

plot main title.

xlab

character vector specifying x and y axis labels, respectively. Use xlab = FALSE and ylab = FALSE to hide xlab and ylab, respectively.

ylab

character vector specifying x and y axis labels, respectively. Use xlab = FALSE and ylab = FALSE to hide xlab and ylab, respectively.

ggtheme

function, ggplot2 theme name. Default value is theme_pubr(). Allowed values include ggplot2 official themes: theme_gray(), theme_bw(), theme_minimal(), theme_classic(), theme_void(), ....

...

other arguments to be passed to ggpar.

Value

returns a ggplot.

Examples

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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 labels
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())