Interactive feature finding in liquid chromatography mass spectrometry data

We propose a method for finding features in liquid chromatography mass spectrometry data that is based on the isotopic pattern of peaks. Our interactive approach to feature finding is carried out across many samples simultaneously and aligns features concurrently. Our scale-independent approach prioritises potential features and is easily adaptable to look for features of a particular mass and charge, paired features in isotopically labeled samples, or differentially expressed features. We demonstrate this by identifying features from normal human adult plasma. We highlight properties of plasma data that illustrate the need to visually check the quality of features found prior to further statistical analysis.