GridMass: a fast two‐dimensional feature detection method for LC/MS |
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Authors: | Victor Treviño Irma‐Luz Yañez‐Garza Carlos E. Rodriguez‐López Rafael Urrea‐López Maria‐Lourdes Garza‐Rodriguez Hugo‐Alberto Barrera‐Saldaña José G. Tamez‐Peña Robert Winkler Rocío‐Isabel Díaz de‐la‐Garza |
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Affiliation: | 1. Cátedra de Bioinformática, Departamento de Investigación e Innovación, Escuela de Medicina, Tecnológico de Monterrey, Guadalupe, Nuevo Leon, Mexico;2. Cátedra de Micronutrientes, Escuela de Biotecnología y Alimentos, Centro de Biotecnología ‐ FEMSA, Tecnológico de Monterrey, Monterrey, Nuevo Leon, Mexico;3. Cátedra Empresarial de Tecnologías de Agricultura Intensiva, Escuela de Biotecnología y Alimentos, Centro de Biotecnología ‐ FEMSA, Tecnológico de Monterrey, Monterrey, Nuevo Leon, Mexico;4. Departamento de Bioquímica y Medicina Molecular, Facultad de Medicina, Universidad Autónoma de Nuevo León, Monterrey, Nuevo Leon, Mexico;5. Departamento of Biotecnología y Bioquímica, CINVESTAV Unidad Irapuato, Irapuato, Guanajuato, Mexico |
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Abstract: | One of the initial and critical procedures for the analysis of metabolomics data using liquid chromatography and mass spectrometry is feature detection. Feature detection is the process to detect boundaries of the mass surface from raw data. It consists of detected abundances arranged in a two‐dimensional (2D) matrix of mass/charge and elution time. MZmine 2 is one of the leading software environments that provide a full analysis pipeline for these data. However, the feature detection algorithms provided in MZmine 2 are based mainly on the analysis of one‐dimension at a time. We propose GridMass, an efficient algorithm for 2D feature detection. The algorithm is based on landing probes across the chromatographic space that are moved to find local maxima providing accurate boundary estimations. We tested GridMass on a controlled marker experiment, on plasma samples, on plant fruits, and in a proteome sample. Compared with other algorithms, GridMass is faster and may achieve comparable or better sensitivity and specificity. As a proof of concept, GridMass has been implemented in Java under the MZmine 2 environment and is available at http://bioinformatica.mty.itesm.mx/GridMass and MASSyPup. It has also been submitted to the MZmine 2 developing community. Copyright © 2015 John Wiley & Sons, Ltd. |
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Keywords: | metabolomics feature detection software & algorithms HPLC/MS MZMine 2 |
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