exploreDDSplot

Scatterplot of transformed counts from two samples or grid of all samples

exploreDDSplot(
  countMatrix,
  targets,
  cmp = cmp[[1]],
  preFilter = NULL,
  samples,
  blind = TRUE,
  scattermatrix = FALSE,
  plotly = FALSE,
  savePlot = FALSE,
  filePlot = NULL
)

Arguments

countMatrix	date.frame or matrix containing raw read counts
targets	targets data.frame
cmp	character matrix where comparisons are defined in two columns. This matrix should be generated with the systemPipeR::readComp() function from the targets file. Values used for comparisons need to match those in the Factor column of the targets file.
preFilter	allows removing rows in which there are very few reads. Accepts a numeric value with the minimum of total reads to keep. Default is NULL.
samples	a character vector of two samples or ALL samples in the dataset. Could be specified the SampleName column name of the targets file or the respective numeric values. Also, if set as ALL, a correlation matrix it will be plot.
blind	logical, whether to blind the transformation to the experimental design (see varianceStabilizingTransformation), from DESeq2::vst() or DESeq2::rlog().
scattermatrix	if samples set as ALL, requires to assign TRUE to build a correlation matrix and plot the correlogram of all the samples.
plotly	logical: when FALSE (default), the ggplot2 plot will be returned. TRUE 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 ggplot2 plot.

Examples

## Targets file
targetspath <- system.file("extdata", "targets.txt", package = "systemPipeR")
targets <- read.delim(targetspath, comment = "#")
cmp <- systemPipeR::readComp(
    file = targetspath,
    format = "matrix", delim = "-"
)
## Count table file
countMatrixPath <- system.file("extdata", "countDFeByg.xls",
    package = "systemPipeR"
)
countMatrix <- read.delim(countMatrixPath, row.names = 1)
## Plot
exploreDDSplot(countMatrix, targets,
    cmp = cmp[[1]], preFilter = NULL,
    samples = c(3, 4)
)