Machine Learning Methods For The Analysis Of Liquid Chromatography Mass Spectrometry Datasets In Metabolomics
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Machine Learning Methods For The Analysis Of Liquid Chromatography Mass Spectrometry Datasets In Metabolomics
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Author : Francesc Fernández Albert
language : en
Publisher:
Release Date : 2014
Machine Learning Methods For The Analysis Of Liquid Chromatography Mass Spectrometry Datasets In Metabolomics written by Francesc Fernández Albert and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Liquid Chromatography-Mass Spectrometry (LC/MS) instruments are widely used in Metabolomics. To analyse their output, it is necessary to use computational tools and algorithms to extract meaningful biological information. The main goal of this thesis is to provide with new computational methods and tools to process and analyse LC/MS datasets in a metabolomic context. A total of 4 tools and methods were developed in the context of this thesis. First, it was developed a new method to correct possible non-linear drift effects in the retention time of the LC/MS data in Metabolomics, and it was coded as an R package called HCor. This method takes advantage of the retention time drift correlation found in typical LC/MS data, in which there are chromatographic regions in which their retention time drift is consistently different than other regions. Our method makes the hypothesis that this correlation structure is monotonous in the retention time and fits a non-linear model to remove the unwanted drift from the dataset. This method was found to perform especially well on datasets suffering from large drift effects when compared to other state-of-the art algorithms. Second, it was implemented and developed a new method to solve known issues of peak intensity drifts in metabolomics datasets. This method is based on a two-step approach in which are corrected possible intensity drift effects by modelling the drift and then the data is normalised using the median of the resulting dataset. The drift was modelled using a Common Principal Components Analysis decomposition on the Quality Control classes and taking one, two or three Common Principal Components to model the drift space. This method was compared to four other drift correction and normalisation methods. The two-step method was shown to perform a better intensity drift removal than all the other methods. All the tested methods including the two-step method were coded as an R package called intCor and it is publicly available. Third, a new processing step in the LC/MS data analysis workflow was proposed. In general, when LC/MS instruments are used in a metabolomic context, a metabolite may give a set of peaks as an output. However, the general approach is to consider each peak as a variable in the machine learning algorithms and statistical tests despite the important correlation structure found between those peaks coming from the same source metabolite. It was developed an strategy called peak aggregation techniques, that allow to extract a measure for each metabolite considering the intensity values of the peaks coming from this metabolite across the samples in study. If the peak aggregation techniques are applied on each metabolite, the result is a transformed dataset in which the variables are no longer the peaks but the metabolites. 4 different peak aggregation techniques were defined and, running a repeated random sub-sampling cross-validation stage, it was shown that the predictive power of the data was improved when the peak aggregation techniques were used regardless of the technique used. Fourth, a computational tool to perform end-to-end analysis called MAIT was developed and coded under the R environment. The MAIT package is highly modular and programmable which ease replacing existing modules for user-created modules and allow the users to perform their personalised LC/MS data analysis workflows. By default, MAIT takes the raw output files from an LC/MS instrument as an input and, by applying a set of functions, gives a metabolite identification table as a result. It also gives a set of figures and tables to allow for a detailed analysis of the metabolomic data. MAIT even accepts external peak data as an input. Therefore, the user can insert peak table obtained by any other available tool and MAIT can still perform all its other capabilities on this dataset like a classification or mining the Human Metabolome Dataset which is included in the package.
Metabolomics
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Author : Wolfram Weckwerth
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-02-04
Metabolomics written by Wolfram Weckwerth and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-04 with Science categories.
Metabolomics: Methods and Protocols examines the state-of-the-art in metabolomic analysis. Leading researchers in the field present protocols for the application of complementary analytical methods, such as gas chromatography-mass spectrometry (GC-MS). Metabolomics: Methods and Protocols contains forward-looking protocols, which provide the essential groundwork for future efforts in elucidating the structure of the unknowns detected in metabolomic studies.
Statistical Analysis Of Proteomics Metabolomics And Lipidomics Data Using Mass Spectrometry
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Author : Susmita Datta
language : en
Publisher: Springer
Release Date : 2016-12-15
Statistical Analysis Of Proteomics Metabolomics And Lipidomics Data Using Mass Spectrometry written by Susmita Datta and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-15 with Medical categories.
This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass spectrometry, time-of-flight data, and Fourier transform mass spectrometry are but a selection of the measurement platforms available to the modern analyst. Thus in practical proteomics or metabolomics, researchers will not only be confronted with new high dimensional data types—as opposed to the familiar data structures in more classical genomics—but also with great variation between distinct types of mass spectral measurements derived from different platforms, which may complicate analyses, comparison, and interpretation of results.
Mass Spectrometry Based Metabolomics
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Author : Sastia Prama Putri
language : en
Publisher: CRC Press
Release Date : 2016-04-21
Mass Spectrometry Based Metabolomics written by Sastia Prama Putri and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-21 with Science categories.
Mass Spectrometry-Based Metabolomics: A Practical Guide is a simple, step-by-step reference for profiling metabolites in a target organism. It discusses optimization of sample preparation for urine, serum, blood, tissue, food, and plant and animal cell samples. Encompassing three different technical fields-biology, analytical chemistry, and informa
Microbial Metabolomics
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Author : Edward E.K. Baidoo
language : en
Publisher: Humana
Release Date : 2018-11-13
Microbial Metabolomics written by Edward E.K. Baidoo and has been published by Humana this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-13 with Science categories.
This detailed volume includes protocols that represent the breadth of microbial metabolomics approaches to both large-scale and small-scale experiments with intention of highlighting techniques that can be used for applications ranging from environmental microbiology to human disease. Utilizing mass spectrometry as their primary measurement tool, the chapters explore microbial metabolomics, metabolism and microbial physiology, metabolite sample preparation, current analytical techniques used to profile primary and secondary metabolites and lipids, as well as establishing data analysis workflows for targeted metabolomics, untargeted metabolomics, analysis of metabolic fluxes, and genome-scale models. Written for the highly successful Methods in Molecular Biology series, chapters include introduction to their respective topics, lists of the necessary materials and reagents, step-by-step readily reproducible protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Microbial Metabolomics: Methods and Protocols serves as an ideal reference for both novice and advanced users and can be adapted to similar analytical platforms or customized to suit the needs of the researcher.
Method Development In Metabolomics
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Author : Oliver Alka
language : en
Publisher:
Release Date : 2023
Method Development In Metabolomics written by Oliver Alka and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
The field of metabolomics is concerned with analyzing data from high-throughput experiments. Its objective is the identification, quantification, and elucidation of the function and interaction of small molecules in a biological system. The prevalent methods used in metabolomics are nuclear magnetic resonance spectroscopy and mass spectrometry. A typical mass spectrometry metabolomics analysis workflow is composed of several steps. First, biological samples are measured using liquid chromatography and mass spectrometry. Second, computational mass spectrometry is used to analyze the acquired data. The results are then stored in a human- readable format, statistically post-processed, and visualized. The driving force of the field is the development of new methods on the analytical and computational side to reach the above-mentioned aims. Nonetheless, there are still some major unsolved issues at different stages of the analysis workflow. Controlling the false-discovery rate (FDR) is well established in other fields (i.e., proteomics), but so far, methods are lacking in the field of metabolomics. This seriously limits the confidence in reported identifications and quantifications, and manual assessment is still common practice. In recent years different methods have been established for untargeted approaches. However, in terms of targeted strategies, the lack of robust FDR estimators prevented the field from obtaining highly confident quantifications. Progress in automating the manual process is substantial to advance targeted metabolomics research and allow proper high-throughput analysis. We established an automated, FDR-controlled targeted analysis workflow that enables a robust FDR estimation for the first time, thus improving the comparability of results in the metabolomics field. Another critical aspect of scientific research is representing and sharing analysis results based on the FAIR principles. The FAIR principles stand for findable, accessible, interoperable, and reusable. In 2014, the human-readable file format MzTab was introduced in the proteomics and metabolomics fields to enable the distribution of analysis results in a standardized open format. However, in recent years, the limitations of this format regarding metabolomics data have become apparent. As part of the Proteomics Standard Initiative, we designed the improved standard MzTab-M that focuses on interoperability and reusability and integrated it into our OpenMS software framework. Metabolomics has a massive range of applications and can be used to answer a variety of scientific questions. The field attempts to answer individual data- and objective-related issues by developing new problem-specific post-processing methods, as we show based on an example in the area of food chemistry. In recent years, the production of primary cacao products, such as cacao butter, moved from Europe to the cacao-producing countries. This leads to the challenge of shifting the quality assessment from raw to primary products to uphold the quality standards and control in the European market. To this end, we provided the basis for such a method by using biomarker identification and machine learning. Using a regression method, we were able to assess the shell quantity in a mixture of bean and shell and, with it, the quality of the product.
Metabolomics
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Author : Ron Wehrens
language : en
Publisher: CRC Press
Release Date : 2019-08-19
Metabolomics written by Ron Wehrens and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-19 with Mathematics categories.
Metabolomics is the scientific study of the chemical processes in a living system, environment and nutrition. It is a relatively new omics science, but the potential applications are wide, including medicine, personalized medicine and intervention studies, food and nutrition, plants, agriculture and environmental science. The topics presented and discussed in this book are based on the European Molecular Biology Organization (EMBO) practical courses in metabolomics bioinformatics taught to those working in the field, from masters to postgraduate students, PhDs, postdoctoral and early PIs. The book covers the basics and fundamentals of data acquisition and analytical technologies, but the primary focus is data handling and data analysis. The mentioning and usage of a particular data analysis tool has been avoided; rather, the focus is on the concepts and principles of data processing and analysis. The material has been class-tested and includes lots of examples, computing and exercises. Key Features: Provides an overview of qualitative /quantitative methods in metabolomics Offers an introduction to the key concepts of metabolomics, including experimental design and technology Covers data handling, processing, analysis, data standards and sharing Contains lots of examples to illustrate the topics Includes contributions from some of the leading researchers in the field of metabolomics with extensive teaching experiences
Processing Metabolomics And Proteomics Data With Open Software
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Author : Robert Winkler
language : en
Publisher: Royal Society of Chemistry
Release Date : 2020-03-19
Processing Metabolomics And Proteomics Data With Open Software written by Robert Winkler and has been published by Royal Society of Chemistry this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-19 with Science categories.
Metabolomics and proteomics allow deep insights into the chemistry and physiology of biological systems. This book expounds open-source programs, platforms and programming tools for analysing metabolomics and proteomics mass spectrometry data. In contrast to commercial software, open-source software is created by the academic community, which facilitates the direct interaction between users and developers and accelerates the implementation of new concepts and ideas. The first section of the book covers the basics of mass spectrometry, experimental strategies, data operations, the open-source philosophy, metabolomics, proteomics and statistics/ data mining. In the second section, active programmers and users describe available software packages. Included tutorials, datasets and code examples can be used for training and for building custom workflows. Finally, every reader is invited to participate in the open science movement.
Sample Preparation In Metabolomics
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Author : Julia Kuligowski
language : en
Publisher: MDPI
Release Date : 2021-04-07
Sample Preparation In Metabolomics written by Julia Kuligowski and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-07 with Medical categories.
Metabolomics is increasingly being used to explore the dynamic responses of living systems in biochemical research. The complexity of the metabolome is outstanding, requiring the use of complementary analytical platforms and methods for its quantitative or qualitative profiling. In alignment with the selected analytical approach and the study aim, sample collection and preparation are critical steps that must be carefully selected and optimized to generate high-quality metabolomic data. This book showcases some of the most recent developments in the field of sample preparation for metabolomics studies. Novel technologies presented include electromembrane extraction of polar metabolites from plasma samples and guidelines for the preparation of biospecimens for the analysis with high-resolution μ magic-angle spinning nuclear magnetic resonance (HR-μMAS NMR). In the following chapters, the spotlight is on sample preparation approaches that have been optimized for diverse bioanalytical applications, including the analysis of cell lines, bacteria, single spheroids, extracellular vesicles, human milk, plant natural products and forest trees.
Metabolomics In Practice
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Author : Michael Lämmerhofer
language : en
Publisher: John Wiley & Sons
Release Date : 2013-02-14
Metabolomics In Practice written by Michael Lämmerhofer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-14 with Science categories.
Unlike other handbooks in this emerging field, this guide focuses on the challenges and critical parameters in running a metabolomics study, including such often-neglected issues as sample preparation, choice of separation and detection method, recording and evaluating data as well as method validation. By systematically covering the entire workflow, from sample preparation to data processing, the insight and advice offered here helps to clear the hurdles in setting up and running a successful analysis, resulting in high-quality data from every experiment. Based on more than a decade of practical experience in developing, optimizing and validating metabolomics approaches as a routine technology in the academic and industrial research laboratory, the lessons taught here are highly relevant for all systems-level approaches, whether in systems biology, biotechnology, toxicology or pharmaceutical sciences. From the Contents: * Sampling and Sample Preparation in Microbial Metabolomics * Tandem Mass Spectrometry Hyphenated with HPLC and UHPLC for Targeted Metabolomics * GC-MS, LC-MS, CE-MS and Ultrahigh Resolution MS (FTICR-MS) in Metabolomics * NMR-based metabolomics analysis * Potential of Microfluidics and Single Cell Analysis in Metabolomics * Data Processing in Metabolomics * Validation and Measurement Uncertainty in Metabolomic Studies * Metabolomics and its Role in the Study of Mammalian Systems and in Plant Sciences * Metabolomics in Biotechnology and Nutritional Metabolomics and more.