Dataset Information

ERah: A computational tool integrating spectral deconvolution and alignment with quantification and identification of metabolites in GCMS- based metabolomics

ABSTRACT: Gas chromatography coupled to mass spectrometry (GC-MS) has been a long- standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex datasets characterized by coeluting compounds and extensive fragmentation of molecular ions caused by the hard electron ionization. In order to identify and extract quantitative information of metabolites across multiple biological samples, integrated computational workflows for data processing are needed. Here we introduce eRah, a free computational tool written in the open language R composed of five core functions: (i) noise filtering and baseline removal of GC-MS chromatograms, (ii) an innovative compound deconvolution process using multivariate analysis techniques based on compound match by local covariance (CMLC) and orthogonal signal deconvolution (OSD), (iii) alignment of mass spectra across samples, (iv) missing compound recovery, and (v) identification of metabolites by spectral library matching using publicly available mass spectra. eRah outputs a table with compound names, matching scores and the integrated area of compounds for each sample. The automated capabilities of eRah are demonstrated by the analysis of GC-TOF MS data from plasma samples of adolescents with hyperinsulinaemic androgen excess and healthy controls. The quantitative results of eRah are compared to centWave, the peak-picking algorithm implemented in the widely used XCMS package, MetAlign and ChromaTOF software. Significantly dysregulated metabolites are further validated using pure standards and targeted analysis by GC-QqQ MS, LC-QqQ and NMR.

INSTRUMENT(S): Agilent 7200 Accurate-Mass Q-TOF

SUBMITTER: Sara Samino

PROVIDER: MTBLS321 | MetaboLights | 2016-09-22

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	MTBLS321	Other
	FILES	Other
	a_MTBLS321_pcos_gc-qtof_metabolite_profiling_mass_spectrometry.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS321_pcos_gc-qtof_metabolite_profiling_mass_spectrometry_v2_maf.tsv	Tabular

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Publications

eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics.

Domingo-Almenara Xavier X Brezmes Jesus J Vinaixa Maria M Samino Sara S Ramirez Noelia N Ramon-Krauel Marta M Lerin Carles C Díaz Marta M Ibáñez Lourdes L Correig Xavier X Perera-Lluna Alexandre A Yanes Oscar O

Analytical chemistry 20160914 19

Gas chromatography coupled to mass spectrometry (GC/MS) has been a long-standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex data sets characterized by coeluting compounds and extensive fragmentation of molecular ions caused by the hard electron ionization. In order to identify and extract quantitative information on metabolite ...[more]

PMID: 27584001

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