spkSlope: Signal Detect Slope Plot

In spkTools: Methods for Spike-in Arrays

Description

Plots observed expression vs. nominal concentration. The overall regression slope, as well as, regression slopes for low, medium, and high bins are computed and the regression lines plotted.

Usage

spkSlope(object, label = NULL, cuts=c(.6,.99), ...)

Arguments

object	a SpikeInExpressionSet object
label	a character string to insert into the plot title
cuts	quantiles used to make the low, medium, and high bins
...	arguments passed to the plot function

Details

The bins are created by computing the proportion of non-spike-in genes with expression values less than or equal to the average expression value at each nominal concentration. Using the default value of cuts, the high bin contains nominal concentrations with 99 percent or more of the non-spike-in expression values lower than it. The medium bin contains nominal concentrations with between 60 and 99 percent of the non-spike-in expression values lower than it. The low bin contains nominal concentrations with less than 60 percent of the non-spike-in expression values lower than it.

Value

avgExp	average expression at each nominal concentration
slopes	the regression slopes - overall and for each bin
breaks	which spike-in levels fall in each bin
brkpts	the expression value of the cut points between bins
prop	the proportion of non-spike-in probes with expression less than the average expression at each nominal concentration

Author(s)

Matthew N. McCall

Examples

data(affy)
spkSlope(affy)

spkTools documentation built on Nov. 8, 2020, 6:55 p.m.