plotNE {rnaseqcomp} | R Documentation |
For each cell line, any compared two replicates might have a portion of transcripts that express in one replicate but not the other, depending on what cutoff is used to define non-express. This function estimate and plot the proportion of disagreement using multiple cutoffs. Average is used when multiple two-replicate comparisons included.
plotNE(dat, steps = seq(-0.5, 12, 0.5), Ks = 0:3, pchK = seq_along(Ks) - 1, plotcell = 1, ...)
dat |
A |
steps |
A numeric vector specifying log-scale cutoffs to be used for calculation and plotting. (default: seq(-0.5, 12, 0.5)) |
Ks |
A numeric vector specifying which cutoffs to be highlighted and to which the reported proportions to be corresponding. |
pchK |
Plot styles of highlight points corresponding
to |
plotcell |
1 or 2 indicating which cell line will be plotted. If values other than 1 and 2, both cell lines will be plotted. This value won't affect estimation for both cell lines. (default: 1) |
... |
Parameters for base function |
plot |
NE plots of quantification pipelines for
selected cell line by |
NE |
A list of two matrices. The first matrix gives
the proportion of disagreement and the second matrix gives the
proportion of both replicates under (non-express)
correspoinding cutoff |
data(simdata) condInfo <- factor(simdata$samp$condition) repInfo <- factor(simdata$samp$replicate) evaluationFeature <- rep(TRUE, nrow(simdata$meta)) calibrationFeature <- simdata$meta$house & simdata$meta$chr == 'chr1' unitReference <- 1 dat <- signalCalibrate(simdata$quant, condInfo, repInfo, evaluationFeature, calibrationFeature, unitReference, calibrationFeature2 = calibrationFeature) plotNE(dat)