plotSD {rnaseqcomp} | R Documentation

## Estimate And Plot Median Standard Deviation

### Description

For each cell line in each pipeline, the standard deviation of detrend logsignals are calculated for individual features. Then, loess smooth on standard deviation are plotted stratified by detrended log signals for select cell line. The median of standard deviation at three different levels of detrend logsignals are reported.

### Usage

    plotSD(dat, constant = 0.5, loessspan = 1/3, thresholds = c(1, 6),
      plotcell = 1, ...)

### Arguments

`dat` | A `rnaseqcomp` S4 class object.
`constant` | A numeric pseudo-constant to be added on all the signals before transferred to log scale. (default: 0.5)
`loessspan` | A numeric number indicating span used for loess smooth. Details see `loess.smooth` function. (Default: 1/3)
`thresholds` | A vector of two numbers define cutoffs for three levels of detreded log signals. (default: c(1, 6))
`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

`plot` | SD plots of quantification pipelines for selected cell line by `plotcell`.
`list` | A list of two matrices of median and standard error of standard deviations.

### Examples

    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)
    plotSD(dat)

[Package rnaseqcomp version 1.14.0 Index]