title: GridMass: a fast two-dimensional feature detection method for LC/MS.
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://www.bioinformatica.mty.itesm.mx/GridMass and MASSyPup. It has also been submitted to the MZmine 2 developing community.
authors.affiliation: Cátedra de Bioinformática, Departamento de Investigación e Innovación, Escuela de Medicina, Tecnológico de Monterrey, Guadalupe, Nuevo Leon, 64849, Mexico.
authors.forename: Victor
authors.initials: V
authors.lastname: Treviño
authors.forename: Irma-Luz
authors.initials: IL
authors.lastname: Yañez-Garza
authors.forename: Carlos E
authors.initials: CE
authors.lastname: Rodriguez-López
authors.forename: Rafael
authors.initials: R
authors.lastname: Urrea-López
authors.forename: Maria-Lourdes
authors.initials: ML
authors.lastname: Garza-Rodriguez
authors.forename: Hugo-Alberto
authors.initials: HA
authors.lastname: Barrera-Saldaña
authors.forename: José G
authors.initials: JG
authors.lastname: Tamez-Peña
authors.forename: Robert
authors.initials: R
authors.lastname: Winkler
authors.forename: Rocío-Isabel
authors.initials: RI
authors.lastname: Díaz de-la-Garza
mesh_terms: D000465:Algorithms; D001769:Blood / Q000378:metabolism; D001774:Blood Chemical Analysis / Q000379:methods; D002212:Capsicum / Q000737:chemistry / Q000378:metabolism; D002853:Chromatography, Liquid / Q000379:methods*; D005189:False Positive Reactions; D005260:Female; D005638:Fruit / Q000737:chemistry; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics / Q000379:methods*; D020543:Proteome; D012815:Signal Processing, Computer-Assisted; D012984:Software
chemical_list: D020543:Proteome
keywords: HPLC/MS; MZMine 2; feature detection; metabolomics; software & algorithms