calcLinear {RPPanalyzer} | R Documentation |
Calculates sample concentrations using linear model fit
Description
calculates sample concentrations of a RPPA data set, using parameter of a linear model fitted to the dilution series.
Usage
calcLinear(x, sample.id = c("sample", "sample.n"), dilution = "dilution"
, method = "quantreg", plot = F, detectionLimit = T)
Arguments
x |
List containing background corrected RPPA data set |
sample.id |
character vector refering to column names from which samples can be separated |
dilution |
column name from the column in feature data that describes the dilution steps of each sample |
method |
character string describing the method used for the linear fit |
plot |
logical. If true dilution curves are plotted |
detectionLimit |
logical. If true model is fitted on dilution steps above the detection limit. If false, all data points are used to fit the model |
Value
expression |
matrix with protein expression data |
dummy |
matrix with protein expression data |
arraydescription |
data frame with feature data |
sampledescription |
data frame with pheno data |
Note
for calculation of serial diluted samples only
Author(s)
Heiko Mannsperger <h.mannsperger@dkfz.de>,Stephan Gade <s.gade@dkfz.de>
Examples
## Not run:
library(RPPanalyzer)
data(ser.dil.samples)
predicted.data <- calcLinear(ser.dil.samples,sample.id=c("sample","sample.n"),
dilution="dilution")
## End(Not run)