Shape-Based Feature Matching Improves Protein Identification via LC-MS and Tandem MS

Abstract The characterization of proteins via liquid chromatography–mass spectrometry (LC-MS) and tandem MS is a challenge due to the large dynamic range and the high complexity of the molecules of interest. In LC-MS experiments, the inconsistent variation in the travel time of analytes in the LC column results in nonlinear shifts in the LC retention time (RT). This variability must be corrected to accurately match corresponding peptide features across samples in LC-MS experiments. Standard methods for RT alignment applied to the raw data are computationally expensive, making it impractical to process a large number of samples. More successful algorithms perform the alignment on features that matched across experiments based on pre-specified mass and RT windows. Features that match across multiple experiments are more likely to be true positives and, therefore, will be more suitable to drive the alignment correction. However, depending on the feature matching algorithm, ambiguities can arise when more tha...