IDPQuantify: Combining Precursor Intensity with Spectral Counts for Protein and Peptide Quantification

Differentiating and quantifying protein
differences in complex
samples produces significant challenges in sensitivity and specificity.
Label-free quantification can draw from two different information
sources: precursor intensities and spectral counts. Intensities are
accurate for calculating protein relative abundance, but values are
often missing due to peptides that are identified sporadically. Spectral
counting can reliably reproduce difference lists, but differentiating
peptides or quantifying all but the most concentrated protein changes
is usually beyond its abilities. Here we developed new software, IDPQuantify,
to align multiple replicates using principal component analysis, extract
accurate precursor intensities from MS data, and combine intensities
with spectral counts for significant gains in differentiation and
quantification. We have applied IDPQuantify to three comparative proteomic
data sets featuring gold standard protein differences spiked in complicated
backgrounds. The software is able to associate peptides with peaks
that are otherwise left unidentified to increase the efficiency of
protein quantification, especially for low-abundance proteins. By
combing intensities with spectral counts from IDPicker, it gains an
average of 30% more true positive differences among top differential
proteins. IDPQuantify quantifies protein relative abundance accurately
in these test data sets to produce good correlations between known
and measured concentrations.