3DSpectra: A 3-dimensional Quantification Algorithm for LC-MS Labeled Profile Data

Biological Significance: Quantitative proteomics is pivotal for many systems biology related fields, such as biomarker discovery. The quantification quality provided by the adopted software is crucial for the success of protein differential expression studies. To determine the reliability of a quantitative computational method, we suggest evaluating performance parameters like accuracy and precision of the quantifications, robustness to outliers and proteome coverage. A quantitative comparison of these parameters is highly desirable since it enables to benchmark software performance. We applied this strategy to 3DSpectra, a 3-dimensional approach to spectra analysis for MS1 peptide quantification. It distinguishes peptide peaks from spurious peaks interfering in the survey scan. 3DSpectra was compared to ASAPRatio in terms of quantification quality performance parameters and showed an overall improvement.