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Comparative Evaluat...
Comparative Evaluation of MS-based Metabolomics Software and Its Application to Preclinical Alzheimer's Disease
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Hao, L. (författare)
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Wang, J. X. (författare)
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Page, D. (författare)
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Asthana, S. (författare)
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- Zetterberg, Henrik, 1973 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för psykiatri och neurokemi,Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry
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Carlsson, C. (författare)
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Okonkwo, O. C. (författare)
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Li, L. J. (författare)
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(creator_code:org_t)
- 2018-06-18
- 2018
- Engelska.
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8
- Relaterad länk:
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https://www.nature.c...
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https://gup.ub.gu.se...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Mass spectrometry-based metabolomics has undergone significant progresses in the past decade, with a variety of software packages being developed for data analysis. However, systematic comparison of different metabolomics software tools has rarely been conducted. In this study, several representative software packages were comparatively evaluated throughout the entire pipeline of metabolomics data analysis, including data processing, statistical analysis, feature selection, metabolite identification, pathway analysis, and classification model construction. LC-MS-based metabolomics was applied to preclinical Alzheimer's disease (AD) using a small cohort of human cerebrospinal fluid (CSF) samples (N = 30). All three software packages, XCMS Online, SIEVE, and Compound Discoverer, provided consistent and reproducible data processing results. A hybrid method combining statistical test and support vector machine feature selection was employed to screen key metabolites, achieving a complementary selection of candidate biomarkers from three software packages. Machine learning classification using candidate biomarkers generated highly accurate and predictive models to classify patients into preclinical AD or control category. Overall, our study demonstrated a systematic evaluation of different MS-based metabolomics software packages for the entire data analysis pipeline which was applied to the candidate biomarker discovery of preclinical AD.
Ämnesord
- NATURVETENSKAP -- Kemi -- Fysikalisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Physical Chemistry (hsv//eng)
Nyckelord
- mild cognitive impairment
- support vector machines
- mass-spectrometry
- data
- database
- tools
- identification
- metabolites
- proteomics
- discovery
- platform
- Science & Technology - Other Topics
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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