MAplot

This function plots log2 fold changes (y-axis) versus the mean of normalized counts (on the x-axis). Statistically significant features are colored.

MAplot(
  degseqDF,
  FDR.cutoff = 0.05,
  comparison,
  filter = c(Fold = 2, FDR = 10),
  genes = "NULL",
  plotly = FALSE,
  savePlot = FALSE,
  filePlot = NULL
)

Arguments

degseqDF	object of class data.frame generated by systemPipeR::run_edgeR() or systemPipeR::run_DESeq2().
FDR.cutoff	filter cutoffs for the p-value adjusted.
comparison	character vector specifying the factor names for comparison.
filter	Named vector with filter cutoffs of format c(Fold=2, FDR=1) where Fold refers to the fold change cutoff (unlogged) and FDR to the p-value cutoff.
genes	character vector of genes names to show on the plot.
plotly	logical: when FALSE (default), the ggplot2 plot will be returned. TRUE option returns the plotly version of the plot.
savePlot	logical: when FALSE (default), the plot will not be saved. If TRUE the plot will be saved, and requires the filePlot argument.
filePlot	file name where the plot will be saved. For more information, please consult the ggplot2::ggsave() function.

Value

returns an object of ggplot or plotly class.

Examples

## Load targets file and count reads dataframe
targetspath <- system.file("extdata", "targets.txt", package = "systemPipeR")
targets <- read.delim(targetspath, comment = "#")
cmp <- systemPipeR::readComp(
    file = targetspath, format = "matrix",
    delim = "-"
)
countMatrixPath <- system.file("extdata", "countDFeByg.xls",
    package = "systemPipeR"
)
countMatrix <- read.delim(countMatrixPath, row.names = 1)
### DEG analysis with `systemPipeR`
degseqDF <- systemPipeR::run_DESeq2(
    countDF = countMatrix, targets = targets,
    cmp = cmp[[1]], independent = FALSE
)
#> Warning: some variables in design formula are characters, converting to factors
DEG_list <- systemPipeR::filterDEGs(
    degDF = degseqDF,
    filter = c(Fold = 2, FDR = 10)
)
## Plot
MAplot(degseqDF,
    comparison = "M12-A12", filter = c(Fold = 1, FDR = 20),
    genes = "ATCG00280"
)