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 covComb_tx_deg
.
DEqual(DE)
a data.frame()
with one column containing the t-statistics from
Differential Expression, typically generated with limma::topTable()
.
The rownames(DE)
should be transcript GENCODE IDs.
a ggplot
object of the DE t-statistic vs
the DE statistic from degradation
## 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)