A DEqual plot compares the effect of RNA degradation from an independent degradation experiment on the y axis to the effect of the outcome of interest. They were orignally described by Jaffe et al, PNAS, 2017 https://doi.org/10.1073/pnas.1617384114. Other DEqual versions are included in Collado-Torres et al, Neuron, 2019 https://doi.org/10.1016/j.neuron.2019.05.013. This function compares your t-statistics of interest computed on transcripts against the t-statistics from degradation time adjusting for the six brain regions from degradation experiment data used for determining rse_tx.

DEqual(
  DE,
  deg_tstats = qsvaR::degradation_tstats,
  show.legend = TRUE,
  show.cor = c("caption", "corner-top", "corner-bottom", "none"),
  font.size = 12,
  cor.size = font.size/2,
  cor.label = "cor: "
)

Arguments

DE

a data.frame() with a column "t" containing the t-statistics from Differential Expression, typically generated with limma::topTable(). rownames(DE) must have transcript Ensembl/Gencode IDs.

deg_tstats

an optional data.frame() with a column "t" containing t-statistics resulted from a degradation experiment. Default is the internal qsvaR::degradation_tstats from the package authors.

show.legend

logical (default TRUE) to show legend in the plot

show.cor

specify where to show the correlation value. Can be one of "caption", "corner-top", "corner-bottom", or "none".

font.size

numeric value to set the base font size of the plot

cor.size

numeric (default font.size/2) to set the font size for the correlation text

cor.label

character (default "cor: ") to set the text preceding the correlation value

Value

a ggplot object of the DE t-statistic vs the DE statistic from degradation

Examples


## Random differential expression t-statistics for the same transcripts
## we have degradation t-statistics for in `degradation_tstats`.
set.seed(101)
random_de <- data.frame(
    t = rt(nrow(degradation_tstats), 5),
    row.names = sample(
        rownames(degradation_tstats),
        nrow(degradation_tstats)
    )
)

## Create the DEqual plot
DEqual(random_de)