iPQF: 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.
An instance of class MSnSet containing
absolute ion intensities.
Vector defining spectra to protein
matching. Generally, this is a feature variable such as
A logical specifying if proteins
being supported by only 1-2 peptide spectra should be filtered
out. Default is FALSE.
Either "none" (don't calculate any
ratios), "sum" (default), or a specific channel (one of
sampleNames(object)) defining how to calculate relative
A logical defining whether to further
use median polish to combine features.
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
A matrix with estimated protein ratios.
iPQF: A new peptide-to-protein summarization method using peptide
characteristics to improve iTRAQ quantification Martina Fischer
and Bernhard Y. Renard, in prep.