dataPreproc {RPPanalyzer} | R Documentation |
Data preprocessing
Description
Function for import, normalization and quality checks of data prior to the actual analysis. The preprocessing steps include subtraction of dilution series intercepts and FCF normalization. Additionally plots for quality checks are generated including dilutions and BLANK measurements.
Usage
dataPreproc(dataDir=getwd(), blocks=12, spot="aushon",
exportNo=3, correct="both", remove_flagged=NULL)
Arguments
dataDir |
directory of gpr files, slidedescription.txt and sampledescription.txt, default is the current working directory |
blocks |
see |
spot |
see |
exportNo |
see |
correct |
"both" applies |
remove_flagged |
Either NULL or an integer. If an integer, looks into column |
Value
A list of 4 elements is returned.
rawdat |
list of 4 raw data elements ( |
cordat |
list of 4 elements like |
normdat |
list of 4 elements like |
DIR |
directory for storing the generated outputs |
All output files are stored in an analysis folder labeled by the date of analysis.
The txt files Dataexpression
and Databackground
result from write.Data
and store the raw data.
The pdf files getIntercepts_Output
and anovaIntercepts_Output
result from correctDilinterc
.
getIntercepts_Output
shows the derived intercepts and smoothing splines of dilution series in dependence of the dilSeriesID
column in sampledescription.txt and the slide/pad/incubationRun/spottingRun columns of the arraydescription
matrix.
anovaIntercepts_Output.pdf
results from the ANOVA in correctDilinterc
, comparing different linear models of the dilution series intercepts. The barplot displays the residual sum of squares (RSS) of the individual model fits. It helps to choose the appropriate exportNo
parameter. As RSS decreases, the model fits better.
Finally, three pdf files for quality checking are returned.
QC_dilutioncurve_raw.pdf
plots target and blank (2nd antibody only) signals from serially diluted control samples of the raw RPPA data set, see plotQC
.
QC_targetVSblank_normed.pdf
plots blank signals vs. target specific signals of dilution intercept corrected and FCF normalized RPPA data, see plotMeasurementsQC
.
QC_qqPlot_normed.pdf
contains qq-plots of dilution intercept corrected and FCF normalized RPPA data, see plotqq
.
Author(s)
Silvia von der Heyde
Examples
## Not run:
library(RPPanalyzer)
# get output list
dataDir<-system.file("extdata",package="RPPanalyzer")
res<-dataPreproc(dataDir=dataDir,blocks=12,spot="aushon",exportNo=4,correct="both")
# get individual elements
# raw data
rawdat<-res$rawdat
# dilution intercept corrected data
cordat<-res$cordat
# dilution intercept corrected and FCF normalized data
normdat<-res$normdat
# output directory
DIR<-res$DIR
## End(Not run)