ArticleBioinformatics (Oxford, England)2014
MetAssign: probabilistic annotation of metabolites from LC-MS data using a Bayesian clustering approach.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data.Briefings in bioinformatics · 2023Article
- Data Processing and Analysis in Mass Spectrometry-Based Metabolomics.Methods in molecular biology (Clifton, N.J.) · 2023Article
- MAVEN2: An Updated Open-Source Mass Spectrometry Exploration Platform.Metabolites · 2022Article
- Recent advances in proteomics and metabolomics in plants.Molecular horticulture · 2022Review
- Strategies for structure elucidation of small molecules based on LC-MS/MS data from complex biological samples.Computational and structural biotechnology journal · 2022Review
- An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group.Analytical chemistry · 2021Article
- Plants Metabolome Study: Emerging Tools and Techniques.Plants (Basel, Switzerland) · 2021Review
- Metabolite discovery through global annotation of untargeted metabolomics data.Nature methods · 2021Article
- Deep annotation of untargeted LC-MS metabolomics data with Binner.Bioinformatics (Oxford, England) · 2020Article
- Metabolomics: A Way Forward for Crop Improvement.Metabolites · 2019Review
- CliqueMS: a computational tool for annotating in-source metabolite ions from LC-MS untargeted metabolomics data based on a coelution similarity network.Bioinformatics (Oxford, England) · 2019Article
- The metaRbolomics Toolbox in Bioconductor and beyond.Metabolites · 2019Review
- Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification.Journal of proteome research · 2018Article
- Advances in metabolome information retrieval: turning chemistry into biology. Part II: biological information recovery.Journal of inherited metabolic disease · 2018Review
- Propagating annotations of molecular networks using in silico fragmentation.PLoS computational biology · 2018Article
- Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome.Analytical and bioanalytical chemistry · 2018Article
- Annotation: A Computational Solution for Streamlining Metabolomics Analysis.Analytical chemistry · 2018Review
- MetaNetter 2: A Cytoscape plugin for ab initio network analysis and metabolite feature classification.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2017Article
- Significance estimation for large scale metabolomics annotations by spectral matching.Nature communications · 2017Article
- Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.Analytical chemistry · 2017Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
motivationThe use of liquid chromatography coupled to mass spectrometry has enabled the high-throughput profiling of the metabolite composition of biological samples. However, the large amount of data obtained can be difficult to analyse and often requires computational processing to understand which metabolites are present in a sample. This article looks at the dual problem of annotating peaks in a sample with a metabolite, together with putatively annotating whether a metabolite is present in the sample. The starting point of the approach is a Bayesian clustering of peaks into groups, each corresponding to putative adducts and isotopes of a single metabolite.
resultsThe Bayesian modelling introduced here combines information from the mass-to-charge ratio, retention time and intensity of each peak, together with a model of the inter-peak dependency structure, to increase the accuracy of peak annotation. The results inherently contain a quantitative estimate of confidence in the peak annotations and allow an accurate trade-off between precision and recall. Extensive validation experiments using authentic chemical standards show that this system is able to produce more accurate putative identifications than other state-of-the-art systems, while at the same time giving a probabilistic measure of confidence in the annotations. AVAILABILITY AND IMPLEMENTATION: The software has been implemented as part of the mzMatch metabolomics analysis pipeline, which is available for download at http://mzmatch.sourceforge.net/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.