Combine multiple ggplot objects into a single layout

The multiplot function arranges multiple ggplot2 objects into a single plotting layout with a specified number of columns.

Usage

multiplot(..., cols = 1)

Arguments

...

One or more ggplot2 objects.

cols

Integer specifying the number of columns in the layout.

Value

A grid object displaying multiple plots arranged in the specified layout.

Details

Multiple ggplot2 objects can be provided either as separate arguments via .... The function uses the grid package to control the layout.

Author

Pedro J. (adapted from https://gist.github.com/pedroj/ffe89c67282f82c1813d)

Examples

# Example using output from TTEST_DDCt
data1 <- read.csv(system.file("extdata", "data_ttest18genes.csv", package = "rtpcr"))
out <- TTEST_DDCt(
  data1,
  paired = FALSE,
  var.equal = TRUE,
  numberOfrefGenes = 1)
#> *** 18 target(s) using 1 reference gene(s) was analysed!
#> *** The Control level was used as calibrator.
  
p1 <- plotFactor(out, 
  x_col = "gene",
  y_col = "log2FC", 
  Lower.se_col = "Lower.se.log2FC",
  Upper.se_col = "Upper.se.log2FC", 
  letters_col = "sig")
  
p2 <- plotFactor(out, 
  x_col = "gene",
  y_col = "RE", 
  Lower.se_col = "Lower.se.RE",
  Upper.se_col = "Upper.se.RE", 
  letters_col = "sig")
  
  

# Example using output from ANOVA_DCt
data2 <- read.csv(system.file("extdata", "data_1factor.csv", package = "rtpcr"))
out2 <- ANOVA_DCt(
  data2,
  numOfFactors = 1,
  numberOfrefGenes = 1,
  block = NULL)
#> 
#> Relative Expression
#> 
#>   gene SA     dCt      RE   log2FC     LCL     UCL      se Lower.se.RE
#> 1   PO L1 1.81000 0.28519 -1.81000 0.18404 0.44193 0.02082     0.28111
#> 2   PO L2 0.67333 0.62706 -0.67333 0.40466 0.97167 0.43880     0.46261
#> 3   PO L3 0.01667 0.98851 -0.01667 0.63792 1.53178 0.08413     0.93252
#>   Upper.se.RE Lower.se.log2FC Upper.se.log2FC sig
#> 1     0.28934        -1.83082        -1.78918   b
#> 2     0.84996        -1.11213        -0.23453   a
#> 3     1.04787        -0.10080         0.06746   a
#> 
#> Note: Using default model for statistical analysis: wDCt ~ SA 
  
df <- out2$relativeExpression

p3 <- plotFactor(
  df,
  x_col = "SA",
  y_col = "RE",
  Lower.se_col = "Lower.se.RE",
  Upper.se_col = "Upper.se.RE",
  letters_col = "sig",
  letters_d = 0.1,
  col_width = 0.7,
  err_width = 0.15,
  fill_colors = "skyblue",
  alpha = 1,
  base_size = 14)

# Combine plots into a single layout
multiplot(p1, p2, cols = 2)


multiplot(p1, p3, cols = 2)