Literature DB >> 27461032

ADAP-GC 3.0: Improved Peak Detection and Deconvolution of Co-eluting Metabolites from GC/TOF-MS Data for Metabolomics Studies.

Yan Ni1, Mingming Su1, Yunping Qiu2, Wei Jia1, Xiuxia Du3.   

Abstract

ADAP-GC is an automated computational pipeline for untargeted, GC/MS-based metabolomics studies. It takes raw mass spectrometry data as input and carries out a sequence of data processing steps including construction of extracted ion chromatograms, detection of chromatographic peak features, deconvolution of coeluting compounds, and alignment of compounds across samples. Despite the increased accuracy from the original version to version 2.0 in terms of extracting metabolite information for identification and quantitation, ADAP-GC 2.0 requires appropriate specification of a number of parameters and has difficulty in extracting information on compounds that are in low concentration. To overcome these two limitations, ADAP-GC 3.0 was developed to improve both the robustness and sensitivity of compound detection. In this paper, we report how these goals were achieved and compare ADAP-GC 3.0 against three other software tools including ChromaTOF, AnalyzerPro, and AMDIS that are widely used in the metabolomics community.

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Year:  2016        PMID: 27461032      PMCID: PMC5544921          DOI: 10.1021/acs.analchem.6b02222

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  6 in total

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2.  ADAP-GC 2.0: deconvolution of coeluting metabolites from GC/TOF-MS data for metabolomics studies.

Authors:  Yan Ni; Yunping Qiu; Wenxin Jiang; Kyle Suttlemyre; Mingming Su; Wenchao Zhang; Wei Jia; Xiuxia Du
Journal:  Anal Chem       Date:  2012-07-12       Impact factor: 6.986

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

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Journal:  J Proteome Res       Date:  2010-09-29       Impact factor: 4.466

4.  MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data.

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Journal:  Bioinformatics       Date:  2006-01-10       Impact factor: 6.937

5.  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

6.  Highly sensitive feature detection for high resolution LC/MS.

Authors:  Ralf Tautenhahn; Christoph Böttcher; Steffen Neumann
Journal:  BMC Bioinformatics       Date:  2008-11-28       Impact factor: 3.169

  6 in total
  11 in total

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Journal:  J Chem Ecol       Date:  2021-01-16       Impact factor: 2.626

2.  Exercise-induced α-ketoglutaric acid stimulates muscle hypertrophy and fat loss through OXGR1-dependent adrenal activation.

Authors:  Yexian Yuan; Pingwen Xu; Qingyan Jiang; Gang Shu; Xingcai Cai; Tao Wang; Wentong Peng; Jiajie Sun; Canjun Zhu; Cha Zhang; Dong Yue; Zhihui He; Jinping Yang; Yuxian Zeng; Man Du; Fenglin Zhang; Lucas Ibrahimi; Sarah Schaul; Yuwei Jiang; Jiqiu Wang; Jia Sun; Qiaoping Wang; Liming Liu; Songbo Wang; Lina Wang; Xiaotong Zhu; Ping Gao; Qianyun Xi; Cong Yin; Fan Li; Guli Xu; Yongliang Zhang
Journal:  EMBO J       Date:  2020-02-27       Impact factor: 11.598

3.  ADAP-GC 4.0: Application of Clustering-Assisted Multivariate Curve Resolution to Spectral Deconvolution of Gas Chromatography-Mass Spectrometry Metabolomics Data.

Authors:  Aleksandr Smirnov; Yunping Qiu; Wei Jia; Douglas I Walker; Dean P Jones; Xiuxia Du
Journal:  Anal Chem       Date:  2019-07-05       Impact factor: 6.986

4.  Contrasting Volatilomes of Livestock Dung Drive Preference of the Dung Beetle Bubas bison (Coleoptera: Scarabaeidae).

Authors:  Nisansala N Perera; Paul A Weston; Russell A Barrow; Leslie A Weston; Geoff M Gurr
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Authors:  Leonardo Perez de Souza; Thomas Naake; Takayuki Tohge; Alisdair R Fernie
Journal:  Gigascience       Date:  2017-07-01       Impact factor: 6.524

Review 6.  Toward a Standardized Strategy of Clinical Metabolomics for the Advancement of Precision Medicine.

Authors:  Nguyen Phuoc Long; Tran Diem Nghi; Yun Pyo Kang; Nguyen Hoang Anh; Hyung Min Kim; Sang Ki Park; Sung Won Kwon
Journal:  Metabolites       Date:  2020-01-29

7.  Metabolomics Analysis of the Development of Sepsis and Potential Biomarkers of Sepsis-Induced Acute Kidney Injury.

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9.  Hepatic Suppression of Mitochondrial Complex II Assembly Drives Systemic Metabolic Benefits.

Authors:  Xueqiang Wang; Weiqiang Lv; Jie Xu; Adi Zheng; Mengqi Zeng; Ke Cao; Xun Wang; Yuting Cui; Hao Li; Meng Yang; Yongping Shao; Fang Zhang; Xuan Zou; Jiangang Long; Zhihui Feng; Jiankang Liu
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10.  Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data.

Authors:  Runmin Wei; Jingye Wang; Mingming Su; Erik Jia; Shaoqiu Chen; Tianlu Chen; Yan Ni
Journal:  Sci Rep       Date:  2018-01-12       Impact factor: 4.379

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