tpptrNormalize: Normalize protein fold changes

Description

Normalizes fold changes determined by TPP-TR experiments over different experimental groups.

Usage

tpptrNormalize(data, normReqs = tpptrDefaultNormReqs(), qcPlotTheme = tppDefaultTheme(), qcPlotPath = NULL, startPars = c(Pl = 0, a = 550, b = 10), maxAttempts = 1, fixedReference = NULL)

Arguments

data

List of ExpressionSets with protein fold changes to be normalized.

normReqs

List of filtering criteria for construction of the normalization set.

qcPlotTheme

ggplot theme for the created plots

qcPlotPath

location where plots of the curves fitted to the normalization set medians should be stored.

startPars

start values for the melting curve parameters. Will be passed to function nls for curve fitting.

maxAttempts

maximal number of curve attempts to fit melting curve to fold change medians when computing normalization factors.

fixedReference

name of a fixed reference experiment for normaliztion. If NULL (default), the experiment with the best R2 when fitting a melting curve through the median fold changes is chosen as the reference.

Value

A list of ExpressionSets storing the normalized data for each experiment. Each ExpressionSet contains the measured fold changes, as well as row and column metadata. In each ExpressionSet S, the fold changes can be accessed by exprs(S). Protein expNames can be accessed by featureNames(S). Isobaric labels and the corresponding temperatures are returned by S$label and S$temperature

Details

Performs normalization of all fold changes in a given list of ExpressionSets. The normalization procedure is described in detail in Savitski et al. (2014). Whether normalization needs to be performed and what method is best suited depends on the experiment. Here we provide a reasonable solution for the data at hand. We distinguish between filtering conditions on fold changes and on additional annotation columns. Correspondingly, normReqs contains two fields, fcFilters and otherFilters. Each entry contains a data frame with three columns specifying the column to be filtered, as well as upper and lower bounds. An example is given by tpptrDefaultNormReqs.

References

Savitski, M. M. and Reinhard, F. BM. and Franken, H. and Werner, T. and Savitski, M. F. and Eberhard, D. and Molina, D. M. and Jafari, R. and Dovega, R. B. and Klaeger, S. and others (2014) Tracking cancer drugs in living cells by thermal profiling of the proteome. Science 346(6205), p. 1255784.

Examples

Run this code

data(hdacTR_smallExample)
tpptrData <- tpptrImport(hdacTR_config, hdacTR_data)
tpptrNorm <- tpptrNormalize(data=tpptrData, normReqs=tpptrDefaultNormReqs())
names(tpptrNorm)

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