calcSdc: Calculates the concentration of serial diluted samples

In RPPanalyzer: Reads, Annotates, and Normalizes Reverse Phase Protein Array Data

Calculates the concentration of serial diluted samples

Description

Calculates the protein concentration of a serial diluted sample stored in an RPPA data list using the serial dilution curve algorithm published by Zhang et.al, Bioinformatics 2009.

Usage

    calcSdc(x,sample.id=c("sample","sample.n"),
		sel=c("measurement","control"), dilution="dilution",
		D0=2,sensible.min=5, sensible.max=1.e9,minimal.err=5,
		plot=T, r=1.2)

Arguments

x	RPPA data list with replicates aggregated with median
sample.id	Attributes to identify the samples
sel	The sample type that should be calculated. Has to be "measurements","control", "neg_control",or "blank".
dilution	Name of the column in the feature data matrix describing the dilution steps of the samples.
D0	Dilution factor.
sensible.min	Signals below this value are marked as undetected
sensible.max	Signals above the value are marked as saturated
minimal.err	Minimal valid estimate for the background noise
plot	Logical. If true, model fits are plotted
r	Constant factor used to determine the confidence interval for the saturation limit $M$ and the background noise $a$, shoul be $>1$. Can be lower if accuracy of signals is improved.

Details

The method of Zhang et. al doesn't fit the dose response curve but a derive model describing the functional relationship between the signals of two consecutive dilution steps. Since this new model does not contain the protein concentration anymore all spots of one array can be used for the fit, allowing a much more robust estimation of the underlying paramters.

Value

expression	matrix with expression values
error	matrix with error values
arraydescription	data frame with feature data
sampledescription	data frame with pheno data

Author(s)

Heiko Mannsperger <[e-mail]>, Stephan Gade <[e-mail]>

References

Zhang et. al, Bioinformatics 2009,Serial dilution curve: a new method for analysis of reverse phase protein array data

Examples

## Not run: 
    library(RPPanalyzer)
    data(ser.dil.samples)

    ser.dil_median <- sample.median(ser.dil.samples)
    predicted.data <- calcSdc(ser.dil_median,D0=2,sel=c("measurement"), dilution="dilution")

## End(Not run)

RPPanalyzer documentation built on Aug. 28, 2023, 5:07 p.m.