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.

同位素标记肽（isotopically labeled peptide）的轻、重同位素变体间的丰度比，可通过其选择离子色谱图（selected ion chromatograms）进行估算。然而，定量鸟枪法蛋白质组学（quantitative shotgun proteomics）的检测会为数以万计的肽段生成信噪比（signal-to-noise ratios）差异极大的选择离子色谱图。这一研究难题亟需既能稳健估算不同肽段的丰度比，又能严格针对各丰度比的预期估计偏差与变异性进行评分的算法。丰度比的评分逻辑与肽段鉴定算法对串联质谱（tandem mass spectra）的序列匹配评分类似，可用于筛选不可靠的肽段定量结果，并在后续的蛋白质丰度比估算中引入严格的统计推断。本研究采用并行配对协方差算法，实现选择离子色谱图中的稳健峰检测。我们为每条肽段生成峰分布图：该分布图为两种同位素变体在其色谱峰内测得的离子强度散点图。本文提出对该峰分布图开展主成分分析（principal component analysis），以估算肽段丰度比，并通过峰分布图信噪比（profile signal-to-noise ratio）对估计结果进行评分。实验结果表明，峰分布图信噪比与肽段丰度比估计的变异性及偏差呈负相关。