title: ADAP-GC 2.0: deconvolution of coeluting metabolites from GC/TOF-MS data for metabolomics studies.
abstract: ADAP-GC 2.0 has been developed to deconvolute coeluting metabolites that frequently exist in real biological samples of metabolomics studies. Deconvolution is based on a chromatographic model peak approach that combines five metrics of peak qualities for constructing/selecting model peak features. Prior to deconvolution, ADAP-GC 2.0 takes raw mass spectral data as input, extracts ion chromatograms for all the observed masses, and detects chromatographic peak features. After deconvolution, it aligns components across samples and exports the qualitative and quantitative information of all of the observed components. Centered on the deconvolution, the entire data analysis workflow is fully automated. ADAP-GC 2.0 has been tested using three different types of samples. The testing results demonstrate significant improvements of ADAP-GC 2.0, compared to the previous ADAP 1.0, to identify and quantify metabolites from gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS) data in untargeted metabolomics studies.
authors: Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, North Carolina Research Campus, Kannapolis, North Carolina 28081, USA.
authors: Yan
authors: Y
authors: Ni
authors: Yunping
authors: Y
authors: Qiu
authors: Wenxin
authors: W
authors: Jiang
authors: Kyle
authors: K
authors: Suttlemyre
authors: Mingming
authors: M
authors: Su
authors: Wenchao
authors: W
authors: Zhang
authors: Wei
authors: W
authors: Jia
authors: Xiuxia
authors: X
authors: Du
mesh_terms: D000465:Algorithms; D001331:Automation; D008401:Gas Chromatography-Mass Spectrometry; D055432:Metabolomics; D012984:Software