title: Maui-VIA: A User-Friendly Software for Visual Identification, Alignment, Correction, and Quantification of Gas Chromatography-Mass Spectrometry Data.
abstract: A current bottleneck in GC-MS metabolomics is the processing of raw machine data into a final datamatrix that contains the quantities of identified metabolites in each sample. While there are many bioinformatics tools available to aid the initial steps of the process, their use requires both significant technical expertise and a subsequent manual validation of identifications and alignments if high data quality is desired. The manual validation is tedious and time consuming, becoming prohibitively so as sample numbers increase. We have, therefore, developed Maui-VIA, a solution based on a visual interface that allows experts and non-experts to simultaneously and quickly process, inspect, and correct large numbers of GC-MS samples. It allows for the visual inspection of identifications and alignments, facilitating a unique and, due to its visualization and keyboard shortcuts, very fast interaction with the data. Therefore, Maui-Via fills an important niche by (1) providing functionality that optimizes the component of data processing that is currently most labor intensive to save time and (2) lowering the threshold of expertise required to process GC-MS data. Maui-VIA projects are initiated with baseline-corrected raw data, peaklists, and a database of metabolite spectra and retention indices used for identification. It provides functionality for retention index calculation, a targeted library search, the visual annotation, alignment, correction interface, and metabolite quantification, as well as the export of the final datamatrix. The high quality of data produced by Maui-VIA is illustrated by its comparison to data attained manually by an expert using vendor software on a previously published dataset concerning the response of Chlamydomonas reinhardtii to salt stress. In conclusion, Maui-VIA provides the opportunity for fast, confident, and high-quality data processing validation of large numbers of GC-MS samples by non-experts.
authors: Integrative Proteomics and Metabolomics, Berlin Institute of Health , Berlin , Germany.
authors: P Henning J L
authors: PH
authors: Kuich
authors: Genome Informatics, Faculty of Technology, CeBiTec, Bielefeld University , Bielefeld , Germany.
authors: Nils
authors: N
authors: Hoffmann
authors: Integrative Proteomics and Metabolomics, Berlin Institute of Health , Berlin , Germany ; Integrative Proteomics and Metabolomics, Berlin Institute for Medical Systems Biology/Max Delbrück Center for Molecular Medicine , Berlin , Germany.
authors: Stefan
authors: S
authors: Kempa
keywords: GC–MS; metabolomics; processing; software
references: Bioinformatics. 2008 Mar 1;24(5):732-7
references: 18204057
references: BMC Genomics. 2012 May 31;13:215
references: 22651860
references: Chem Soc Rev. 2011 Jan;40(1):387-426
references: 20717559
references: Anal Chem. 2005 Sep 1;77(17):5635-42
references: 16131076
references: Anal Chem. 2006 Feb 1;78(3):779-87
references: 16448051
references: Phytochemistry. 2003 Mar;62(6):817-36
references: 12590110
references: Cancer Metab. 2014 Jun 30;2:9
references: 25035808
references: J Chromatogr. 1963 Aug;11:463-71
references: 14062605
references: Bioinformatics. 2014 Apr 1;30(7):988-95
references: 24363380
references: Mol Cell Proteomics. 2011 Jan;10(1):R110.000133
references: 20716697
references: Annu Rev Anal Chem (Palo Alto Calif). 2010;3:433-65
references: 20636050
references: Analyst. 2012 Jan 21;137(2):293-300
references: 22102985
references: J Chromatogr B Analyt Technol Biomed Life Sci. 2008 Aug 15;871(2):182-90
references: 18501684
references: J Chromatogr A. 2014 Sep 5;1358:155-64
references: 25063004
references: Anal Chem. 2009 Apr 15;81(8):3079-86
references: 19301908
references: Nat Protoc. 2006;1(1):387-96
references: 17406261
references: BMC Bioinformatics. 2010 Jul 23;11:395
references: 20650010
references: BMC Bioinformatics. 2012 Aug 27;13:214
references: 22920415