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GridMass: a fast two‐dimensional feature detection method for LC/MS
Author(s) -
Treviño Victor,
YañezGarza IrmaLuz,
RodriguezLópez Carlos E.,
UrreaLópez Rafael,
GarzaRodriguez MariaLourdes,
BarreraSaldaña HugoAlberto,
TamezPeña José G.,
Winkler Robert,
Díaz delaGarza RocíoIsabel
Publication year - 2015
Publication title -
journal of mass spectrometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 121
eISSN - 1096-9888
pISSN - 1076-5174
DOI - 10.1002/jms.3512
Subject(s) - chemistry , feature (linguistics) , pipeline (software) , chromatography , mass spectrometry , software , matrix (chemical analysis) , java , principal component analysis , pattern recognition (psychology) , analytical chemistry (journal) , artificial intelligence , computer science , philosophy , linguistics , programming language
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.