Literature DB >> 23885350

A method of aligning peak lists generated by gas chromatography high-resolution mass spectrometry.

Xiaoli Wei1, Xue Shi, Mark Merrick, Peter Willis, David Alonso, Xiang Zhang.   

Abstract

We report a method for the peak list alignment of gas chromatography high resolution time-of-flight mass spectrometry data. The alignment is performed in a z-score transformed retention time domain to standardize chromatographic peak distribution across samples. A mixture score is developed to assess the similarity between two peaks by simultaneously evaluating the mass spectral similarity and the closeness of retention time. An analysis of experimental data acquired under three different flow rates indicates that the proposed method is able to correctly align the heterogeneous data. The effectiveness of method is further validated by analyzing experimental data of multiple mixtures of metabolite extract from mouse liver with 28 spiked-in acids. All of the detected spiked-in acids were correctly aligned. A statistical test correctly detected the concentration differences of the spiked-in compounds between sample groups using the alignment table. The area under curve (AUC) value in the receiver operating characteristic (ROC) curve is larger than 0.85 in all three of the compared sample groups, indicating a high accuracy of peak alignment and supporting the potential application of the proposed method for metabolomics projects such as biomarker discovery.

Entities:  

Mesh:

Year:  2013        PMID: 23885350      PMCID: PMC3933976          DOI: 10.1039/c3an00667k

Source DB:  PubMed          Journal:  Analyst        ISSN: 0003-2654            Impact factor:   4.616


  16 in total

1.  Parametric time warping.

Authors:  Paul H C Eilers
Journal:  Anal Chem       Date:  2004-01-15       Impact factor: 6.986

2.  A method of finding optimal weight factors for compound identification in gas chromatography-mass spectrometry.

Authors:  Seongho Kim; Imhoi Koo; Xiaoli Wei; Xiang Zhang
Journal:  Bioinformatics       Date:  2012-02-13       Impact factor: 6.937

3.  MSeasy: unsupervised and untargeted GC-MS data processing.

Authors:  Florence Nicolè; Yann Guitton; Elodie A Courtois; Sandrine Moja; Laurent Legendre; Martine Hossaert-McKey
Journal:  Bioinformatics       Date:  2012-07-10       Impact factor: 6.937

4.  An automated data analysis pipeline for GC-TOF-MS metabonomics studies.

Authors:  Wenxin Jiang; Yunping Qiu; Yan Ni; Mingming Su; Wei Jia; Xiuxia Du
Journal:  J Proteome Res       Date:  2010-09-29       Impact factor: 4.466

5.  Data pre-processing in liquid chromatography-mass spectrometry-based proteomics.

Authors:  Xiang Zhang; John M Asara; Jiri Adamec; Mourad Ouzzani; Ahmed K Elmagarmid
Journal:  Bioinformatics       Date:  2005-09-08       Impact factor: 6.937

6.  Optimization and testing of mass spectral library search algorithms for compound identification.

Authors:  S E Stein; D R Scott
Journal:  J Am Soc Mass Spectrom       Date:  1994-09       Impact factor: 3.109

7.  DISCO: distance and spectrum correlation optimization alignment for two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics.

Authors:  Bing Wang; Aiqin Fang; John Heim; Bogdan Bogdanov; Scott Pugh; Mark Libardoni; Xiang Zhang
Journal:  Anal Chem       Date:  2010-06-15       Impact factor: 6.986

8.  An optimal peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using mixture similarity measure.

Authors:  Seongho Kim; Aiqin Fang; Bing Wang; Jaesik Jeong; Xiang Zhang
Journal:  Bioinformatics       Date:  2011-04-14       Impact factor: 6.937

9.  GC-MS-based metabolomics reveals mechanism of action for hydrazine induced hepatotoxicity in rats.

Authors:  Kiyoko Bando; Takeshi Kunimatsu; Jun Sakai; Juki Kimura; Hitoshi Funabashi; Takaki Seki; Takeshi Bamba; Eiichiro Fukusaki
Journal:  J Appl Toxicol       Date:  2010-12-10       Impact factor: 3.446

10.  MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data.

Authors:  Tomás Pluskal; Sandra Castillo; Alejandro Villar-Briones; Matej Oresic
Journal:  BMC Bioinformatics       Date:  2010-07-23       Impact factor: 3.169

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