Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control View Full Text


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Article Info

DATE

2014-06-10

AUTHORS

Jennifer A Kirwan, Ralf J M Weber, David I Broadhurst, Mark R Viant

ABSTRACT

Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment. More... »

PAGES

140012

References to SciGraph publications

  • 2007-09. The metabolomics standards initiative (MSI) in METABOLOMICS
  • 2007-09. Proposed minimum reporting standards for data analysis in metabolomics in METABOLOMICS
  • 2011-07. Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry in NATURE PROTOCOLS
  • 2007-12. Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation in BMC BIOINFORMATICS
  • 2013-06. Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow in ANALYTICAL AND BIOANALYTICAL CHEMISTRY
  • 2008-06. Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry in METABOLOMICS
  • 2012-10. MetaboLights: towards a new COSMOS of metabolomics data management in METABOLOMICS
  • 2008-10-23. Systems biology: Metabonomics in NATURE
  • 2013-03. Flow infusion electrospray ionisation mass spectrometry for high throughput, non-targeted metabolite fingerprinting: a review in METABOLOMICS
  • 2007-09. Proposed minimum reporting standards for chemical analysis in METABOLOMICS
  • 2009-06. A signal filtering method for improved quantification and noise discrimination in fourier transform ion cyclotron resonance mass spectrometry-based metabolomics data in JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
  • 2009-02. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression in NATURE
  • 2012-06. Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline in METABOLOMICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/sdata.2014.12

    DOI

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    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/25977770


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