volcanoplot | R Documentation |
volcanoplot
A simple function that shows statistical significance
(p-value
) versus magnitude of change (log2 fold change
).
volcanoplot( degseqDF, comparison, filter = c(Fold = 2, FDR = 10), genes = "NULL", plotly = FALSE, savePlot = FALSE, filePlot = NULL )
degseqDF |
object of class |
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 |
|
plotly |
logical: when |
savePlot |
logical: when |
filePlot |
file name where the plot will be saved. For more information,
please consult the |
returns an object of ggplot
or plotly
class.
## 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) DEG_list <- systemPipeR::filterDEGs( degDF = degseqDF, filter = c(Fold = 2, FDR = 10)) ## Plot volcanoplot(degseqDF, comparison = "M12-A12", filter = c(Fold = 1, FDR = 20), genes = "ATCG00280")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.