Alignment of LC-MS Data Using Peptide Features



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Integrated liquid-chromatography mass-spectrometry(LC-MS) is becoming a widely used approach for quantifying the protein composition of complex samples.In the last few years,this technology has been used to compare complex biological samples across multiple conditions. One challenge in the analysis of an LC-MS experiment is the alignment of peptide features across samples. In this paper,we proposed a new method using the peptide internal information (both LC-MS and LC-MS/MS information) to align features from multiple LC-MS experiments.We defined Anchor points which are data elements that are highly confident we have identified and are shared by both samples. We chose one sample as template data set, find Anchor points in this sample, then apply alignment to modify another sample, find Anchors in modified sample, these Anchors should line up with one another. One advantage of our method is that it allows statistical assessment of alignment performance. Use anchor points to perform alignment between samples, and labeling an objective performance in LC-MS.