Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway an...Continue Reading
XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification
A pragmatic and readily implemented quality control strategy for HPLC-MS and GC-MS-based metabonomic analysis
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Optimization and evaluation of metabolite extraction protocols for untargeted metabolic profiling of liver samples by UPLC-MS
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Objective set of criteria for optimization of sample preparation procedures for ultra-high throughput untargeted blood plasma lipid profiling by ultra performance liquid chromatography-mass spectrometry
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The BUME method: a new rapid and simple chloroform-free method for total lipid extraction of animal tissue
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Expanding Lipidome Coverage Using LC-MS/MS Data-Dependent Acquisition with Automated Exclusion List Generation
Unsupervised Discovery and Comparison of Structural Families Across Multiple Samples in Untargeted Metabolomics
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Detailed Investigation and Comparison of the XCMS and MZmine 2 Chromatogram Construction and Chromatographic Peak Detection Methods for Preprocessing Mass Spectrometry Metabolomics Data
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Validating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography-High-Resolution Mass Spectrometry Platforms
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SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery
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The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments
Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies
One- vs two-phase extraction: re-evaluation of sample preparation procedures for untargeted lipidomics in plasma samples
Early Life Interventions for Childhood Growth and Development in Tanzania (ELICIT): a protocol for a randomised factorial, double-blind, placebo-controlled trial of azithromycin, nitazoxanide and nicotinamide
Toward Reproducible Results from Targeted Metabolomic Studies: Perspectives for Data Pre-processing and a Basis for Analytic Pipeline Development
Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches
XCMS-MRM and METLIN-MRM: a cloud library and public resource for targeted analysis of small molecules
Mind the Gap: Mapping Mass Spectral Databases in Genome-Scale Metabolic Networks Reveals Poorly Covered Areas
A global HILIC-MS approach to measure polar human cerebrospinal fluid metabolome: Exploring gender-associated variation in a cohort of elderly cognitively healthy subjects
The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease
Impact of Blood Collection Tubes and Sample Handling Time on Serum and Plasma Metabolome and Lipidome
Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies
Impact of post-collection freezing delay on the reliability of serum metabolomics in samples reflecting the California mid-term pregnancy biobank
The Effect of Anticoagulants, Temperature, and Time on the Human Plasma Metabolome and Lipidome from Healthy Donors as Determined by Liquid Chromatography-Mass Spectrometry
Merged Targeted Quantification and Untargeted Profiling for Comprehensive Assessment of Acylcarnitine and Amino Acid Metabolism
DecoMetDIA: Deconvolution of Multiplexed MS/MS Spectra for Metabolite Identification in SWATH-MS-Based Untargeted Metabolomics
Enhancing Metabolome Coverage in Data-Dependent LC-MS/MS Analysis through an Integrated Feature Extraction Strategy
Comparing Targeted vs. Untargeted MS2 Data-Dependent Acquisition for Peak Annotation in LC-MS Metabolomics
Network based strategies in metabolomics data analysis and interpretation: from molecular networking to biological interpretation
Lipid Annotation by Combination of UHPLC-HRMS (MS), Molecular Networking, and Retention Time Prediction: Application to a Lipidomic Study of In Vitro Models of Dry Eye Disease
Targeting unique biological signals on the fly to improve MS/MS coverage and identification efficiency in metabolomics.
Single-Step Extraction Coupled with Targeted HILIC-MS/MS Approach for Comprehensive Analysis of Human Plasma Lipidome and Polar Metabolome
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Metabolomics for Biomarker Discovery: Key Signatory Metabolic Profiles for the Identification and Discrimination of Oat Cultivars.
Increased inosine levels in drug-free individuals with at-risk mental state: A serum metabolomics study.
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