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

Yan Ni, Yunping Qiu, Wenxin Jiang, Kyle Suttlemyre, Mingming Su, Wenchao Zhang, Wei Jia, Xiuxia Du

Research output: Contribution to journalArticlepeer-review

63 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)6619-6629
Number of pages11
JournalAnalytical Chemistry
Issue number15
StatePublished - Aug 7 2012
Externally publishedYes

ASJC Scopus subject areas

  • Analytical Chemistry


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