plot_ma: MA-plot from base means and log fold changes

In baj12/idealImmunoTP: Interactive Differential Expression AnaLysis

MA-plot from base means and log fold changes

Description

MA-plot from base means and log fold changes, in the ggplot2 framework, with additional support to annotate genes if provided.

Usage

plot_ma(
  res_obj,
  FDR = 0.05,
  point_alpha = 0.2,
  sig_color = "red",
  annotation_obj = NULL,
  hlines = NULL,
  title = NULL,
  xlab = "mean of normalized counts - log10 scale",
  ylim = NULL,
  add_rug = TRUE,
  intgenes = NULL,
  intgenes_color = "steelblue",
  labels_intgenes = TRUE,
  labels_repel = TRUE
)

Arguments

res_obj	A DESeqResults object
FDR	Numeric value, the significance level for thresholding adjusted p-values
point_alpha	Alpha transparency value for the points (0 = transparent, 1 = opaque)
sig_color	Color to use to mark differentially expressed genes. Defaults to red
annotation_obj	A data.frame object, with row.names as gene identifiers (e.g. ENSEMBL ids) and a column, gene_name, containing e.g. HGNC-based gene symbols. Optional
hlines	The y coordinate (in absolute value) where to draw horizontal lines, optional
title	A title for the plot, optional
xlab	X axis label, defaults to "mean of normalized counts - log10 scale"
ylim	Vector of two numeric values, Y axis limits to restrict the view
add_rug	Logical, whether to add rug plots in the margins
intgenes	Vector of genes of interest. Gene symbols if a symbol column is provided in res_obj, or else the identifiers specified in the row names
intgenes_color	The color to use to mark the genes on the main plot.
labels_intgenes	Logical, whether to add the gene identifiers/names close to the marked plots
labels_repel	Logical, whether to use geom_text_repel for placing the labels on the features to mark

Details

The genes of interest are to be provided as gene symbols if a symbol column is provided in res_obj, or else b< using the identifiers specified in the row names

Value

An object created by ggplot

Examples

library(airway)
data(airway)
airway
dds_airway <- DESeq2::DESeqDataSetFromMatrix(assay(airway),
                                             colData = colData(airway),
                                             design=~cell+dex)
# subsetting for quicker run, ignore the next two commands if regularly using the function 
gene_subset <- c(
  "ENSG00000103196",  # CRISPLD2
  "ENSG00000120129",  # DUSP1
  "ENSG00000163884",  # KLF15
  "ENSG00000179094",  # PER1
  rownames(dds_airway)[rep(c(rep(FALSE,99), TRUE), length.out=nrow(dds_airway))]) # 1% of ids
dds_airway <- dds_airway[gene_subset,]
                  
dds_airway <- DESeq2::DESeq(dds_airway)
res_airway <- DESeq2::results(dds_airway)

plot_ma(res_airway, FDR = 0.05, hlines = 1)

plot_ma(res_airway, FDR = 0.1,
        intgenes = c("ENSG00000103196",  # CRISPLD2
                     "ENSG00000120129",  # DUSP1
                     "ENSG00000163884",  # KLF15
                     "ENSG00000179094")  # PER1
       )

baj12/idealImmunoTP documentation built on Nov. 19, 2024, 11:11 a.m.