Learn R Programming

rnaseqcomp (version 1.2.2)

plotNE: Estimate And Plot Express And Non-express Features

Description

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.

Usage

plotNE(dat, steps = seq(-0.5, 12, 0.5), Ks = 0:3, pchK = seq_along(Ks) -
  1, plotcell = 1, ...)

Arguments

dat
A rnaseqcomp S4 class object.
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 Ks. (default: seq_along(Ks) - 1)
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.

Value

  • plotNE plots of quantification pipelines for selected cell line by plotcell.
  • NEA 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 Ks. Values are based on average of two cell lines.

Examples

Run this code
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)

Run the code above in your browser using DataLab