iPQF

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iPQF: iTRAQ (and TMT) Protein Quantification based on Features

The iPQF spectra-to-protein summarisation method integrates peptide spectra characteristics and quantitative values for protein quantitation estimation. Spectra features, such as charge state, sequence length, identification score and others, contain valuable information concerning quantification accuracy. The iPQF algorithm assigns weights to spectra according to their overall feature reliability and computes a weighted mean to estimate protein quantities. See also combineFeatures for a more general overview of feature aggregation and examples.

Usage
iPQF(object, groupBy, low.support.filter = FALSE, ratio.calc = "sum", method.combine = FALSE, feature.weight = c(7, 6, 4, 3, 2, 1, 5)^2)
Arguments
object
An instance of class MSnSet containing absolute ion intensities.
groupBy
Vector defining spectra to protein matching. Generally, this is a feature variable such as fData(object)$accession. low.support.filter A logical specifying if proteins being supported by only 1-2 peptide spectra should be filtered out. Default is FALSE. ratio.calc Either "none" (don't calculate any ratios), "sum" (default), or a specific channel (one of sampleNames(object)) defining how to calculate relative peptides intensities. method.combine A logical defining whether to further use median polish to combine features. feature.weight Vector "numeric" giving weight to the different features. Default is the squared order of the features redundant -unique-distance metric, charge state, ion intensity, sequence length, identification score, modification state, and mass based on a robustness analysis. Value A matrix with estimated protein ratios. References iPQF: A new peptide-to-protein summarization method using peptide characteristics to improve iTRAQ quantification Martina Fischer and Bernhard Y. Renard, in prep. Aliases • iPQF Examples data(msnset2) head(exprs(msnset2)) prot <- combineFeatures(msnset2, groupBy = fData(msnset2)$accession,
fun = "iPQF")