View source: R/normalizeRPPA.R
normalizeRPPA | R Documentation |
Normalizes data in an RPPA data list. Four different normalization methods are provided: using externally measured protein concentration, signals from housekeeping proteins or protein dyes and row normalization.
normalizeRPPA(x, method = "row", normalizer = "housekeeping", useCol = "BCA",
writetable = F,vals="logged")
x |
List containing RPPA data set |
method |
character string: one of |
normalizer |
character string describing the target in slidedescription
that should be used for normalization using |
useCol |
character string describing the column in sampledescription
that should be used for normalization using the method |
writetable |
logical. If true data are exported as tab delimited text files to current working directory |
vals |
the data is returned at log2 scale with substracted normalizer
value per default. If argument is set to |
The function provides four different methods to normalize RPPA data to ensure
that an optimal data quality. The default method row
uses the expression
matrix: after taking the logarithm the row median is substracted from each
value of one row assuming that the median expression over all targets of one
sample is representing total protein amount of the spots. For the method
proteinDye
arrays with the pattern protein
in the target
description are used for normalization. For every spotting run a separate
protein slide is required. If the slides containing more than one array, the
arrays will be normalized by the corresponding protein
array. To use
external protein assay data for normalization, a column containing the protein
concentration has to be added to the sampledescription file. The name of this
column is addressed via the useCol
argument. To use any other target
for normalization the method housekeeping
can be used. The target
for this method has to be addressed via the normalizer
argument.
expression |
matrix with protein expression data |
dummy |
matrix with protein expression data |
arraydescription |
data frame with feature data |
sampledescription |
data frame with pheno data |
Heiko Mannsperger <h.mannsperger@dkfz-heidelberg.de>
## Not run:
library(RPPanalyzer)
data(dataI)
dataI_bgcorr <- correctBG(dataI,method="normexp")
dataIb <- pick.high.conc(dataI_bgcorr,highest="dilution")
normRow <- normalizeRPPA(dataIb,method="row")
normDye <- normalizeRPPA(dataIb,method="proteinDye")
normPassay <- normalizeRPPA(dataIb,method="extValue",useCol="concentration")
normHK <- normalizeRPPA(dataIb,method="housekeeping",normalizer="housekeeping")
## End(Not run)
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