Robust Estimation of Peptide Abundance Ratios and Rigorous Scoring of Their Variability and Bias in Quantitative Shotgun Proteomics

The abundance ratio between the light and heavy isotopologues of an isotopically labeled peptide can be
estimated from their selected ion chromatograms. However, quantitative shotgun proteomics measurements
yield selected ion chromatograms at highly variable signal-to-noise ratios for tens of thousands of peptides. This
challenge calls for algorithms that not only robustly
estimate the abundance ratios of different peptides but
also rigorously score each abundance ratio for the expected estimation bias and variability. Scoring of the
abundance ratios, much like scoring of sequence assignment for tandem mass spectra by peptide identification
algorithms, enables filtering of unreliable peptide quantification and use of formal statistical inference in the
subsequent protein abundance ratio estimation. In this
study, a parallel paired covariance algorithm is used for
robust peak detection in selected ion chromatograms. A
peak profile is generated for each peptide, which is a
scatterplot of ion intensities measured for the two isotopologues within their chromatographic peaks. Principal
component analysis of the peak profile is proposed to
estimate the peptide abundance ratio and to score the
estimation with the signal-to-noise ratio of the peak profile
(profile signal-to-noise ratio). We demonstrate that the
profile signal-to-noise ratio is inversely correlated with the
variability and bias of peptide abundance ratio estimation.