Algorithms and tools for the preprocessing of LC-MS metabolomics data

Metabolomics encompasses the study of small molecules in a biological sample. Liquid Chromatography coupled with Mass Spectrometry (LC-MS) profiling is an important approach for the identification and quantification of metabolites from complex biological samples. The amount and complexity of data produced in an LC-MS profiling experiment demand automatic tools for the preprocessing, analysis, and extraction of useful biological information. Data preprocessing-a topic that covers noise filtering, peak detection, deisotoping, alignment, identification, and normalization-is thus an active area of metabolomics research. Recent years have witnessed development of many software for data preprocessing, and still there is a need for further improvement of the data preprocessing pipeline. This review presents an overview of selected software tools for preprocessing LC-MS based metabolomics data and tries to provide future directions. (c) 2011 Elsevier B.V. All rights reserved.