Testing for RNA dropout of a 4sU sample is performed by comparing half-lives or NTR ranks against the log2 fold change of the 4sU sample vs equivalent no4sU samples.
Plot4sUDropoutRankAll(data, pairs = Findno4sUPairs(data), ...)Plot4sUDropoutAll(data, pairs = Findno4sUPairs(data), ...)
Plot4sUDropoutDeferAll(data, pairs = NULL, ...)
Plot4sUDropoutRankDeferAll(data, pairs = NULL, ...)
Plot4sUDropoutRank(
data,
w4sU,
no4sU = Findno4sUPairs(data)[[w4sU]],
ntr = w4sU,
ylim = NULL,
LFC.fun = lfc::PsiLFC,
slot = "count",
correction = 1,
label.corr = TRUE,
return.corr = FALSE,
boxplot.bins = 10,
title = w4sU,
size = 1.5,
invert.ranks = FALSE
)
Plot4sUDropout(
data,
w4sU,
no4sU = Findno4sUPairs(data)[[w4sU]],
ntr = w4sU,
ylim = NULL,
LFC.fun = lfc::PsiLFC,
slot = "count",
hl.quantile = 0.8,
hl = NULL,
correction = 1,
label.corr = FALSE,
return.corr = FALSE,
title = w4sU,
size = 1.5,
color.by.ntr = FALSE
)
either a ggplot object, a list of ggplot objects, or a list of deferred functions for plotting
a grandR object
a no4sU pairs list as generated by Findno4sUPairs
further arguments to be passed to or from other methods.
the name of a 4sU sample
the name(s) of equivalent no4sU sample(s)
the name of a sample to take NTRs from (usually equal to w4sU)
y axis limits
function to compute log fold change (default: PsiLFC, other viable option: NormLFC)
the slot of the grandR object to take the data from; for PsiLFC, this really should be "count"!
correction factor
add statistics as subtitle
instead of only the ggplot object, return a list with slots plot (what is normally returned) and label (the correlation statistics)
how many boxplots for Plot4sUDropoutRank
the main title for the plot
the point size
if TRUE, left to right on the plot is largest NTR to smallest NTR
the half-life quantile to cut the plot
if NULL, compute half-lives from the ntr column; otherwise, must be a vector containing half-lives
if true, compute the density colors along the ntr axis instead of globally
The deferred versions are useful to be used in conjunction with ServeGrandR plot.static. Their implementation make sure that they are lightweight, i.e. when saving the returned function to an Rdata file, the grandR object is not stored.
Findno4sUPairs,Defer