volcanoPair: Scatter plot of log2 fold changes.
In jtlovell/RNAseqDE: A pipeline for differential expression analyses in R

Description Usage Arguments Details Value Examples

volcanoPair Make an expression volcano plot from log2-fold change and p-value data

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volcanoPair(lfc1, lfc2, legpos = "topleft", leginset = c(0, 0),
  legcex = 1, pt.col = NULL, pt.pch = NULL, pt.cex = NULL,
  line.col = "grey", line.lty = 2, line.lwd = 1, ...)

`lfc1`	A vector of log-2 fold change (or similar data) for the x axis
`lfc2`	A vector of log-2 fold change (or similar data) for the y axis
`legpos`	The position of the legend. Defaults to the top right.
`...`	additional arguments passed on to plot
`cols`	A vector of colors, if specified, overrides all other coloring parameters
`sig1`	Either a 0/1 binary vector of significance, or a vector of transformed p-values for coloring the x axis points
`sig2`	Either a 0/1 binary vector of significance, or a vector of transformed p-values for coloring the y axis points
`alpha`	If providing a vector of transformed p-values, this specifies the threshold for siginficance. Otherwise, not used.
`pointcols`	Vector of legnth 4. Indicates the color of significant points for both [1], just the y axis [2], just the x axis [3] or neighter.
`pchs`	Follows pointcols for point shapes
`cex`	Follows pointcols for point sizes

Using base R graphics, this function tabulates the number of significant values and plots

a table with the number of significant effects

## Not run: 
data(kidney) #from the simseq package
counts<-kidney$counts
counts<-counts[sample(1:nrow(counts),1000),]
info<-data.frame(rep=kidney$replic, treatment=kidney$treatment)
stats<-pipeLIMMA(counts=counts, info=info,
                 formula = " ~ treatment + rep",
                 block=NULL, getTopTable=T, getEbayes=T)
stats<-stats$stats
volcanoPair(lfc1=stats$treatmentTumor_logFC,
           lfc2=stats$rep6090_logFC,
            sig1=stats$ebayesQvalue_treatmentTumor,
            sig2=stats$ebayesQvalue_rep6090)

## End(Not run)