Statistical Analysis Of Proteomics Metabolomics And Lipidomics Data Using Mass Spectrometry

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.

This is an in-depth guide to the theory and practice of analyzing raw mass spectrometry (MS) data in proteomics. The volume outlines available bioinformatics programs, algorithms, and databases available for MS data analysis. General guidelines for data analysis using search engines such as Mascot, Xtandem, and VEMS are provided, with specific attention to identifying poor quality data and optimizing search parameters.

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.

The definitive introduction to data analysis in quantitative proteomics This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative proteomics experiments. The author’s carefully constructed approach allows readers to easily make the transition into the field of quantitative proteomics. Through detailed descriptions of wet-lab methods, computational approaches and statistical tools, this book covers the full scope of a quantitative experiment, allowing readers to acquire new knowledge as well as acting as a useful reference work for more advanced readers. Computational and Statistical Methods for Protein Quantification by Mass Spectrometry: Introduces the use of mass spectrometry in protein quantification and how the bioinformatics challenges in this field can be solved using statistical methods and various software programs. Is illustrated by a large number of figures and examples as well as numerous exercises. Provides both clear and rigorous descriptions of methods and approaches. Is thoroughly indexed and cross-referenced, combining the strengths of a text book with the utility of a reference work. Features detailed discussions of both wet-lab approaches and statistical and computational methods. With clear and thorough descriptions of the various methods and approaches, this book is accessible to biologists, informaticians, and statisticians alike and is aimed at readers across the academic spectrum, from advanced undergraduate students to post doctorates entering the field.

This book explores the most important processing steps of proteomics data analysis and presents practical guidelines, as well as software tools, that are both user-friendly and state-of-the-art in chemo- and biostatistics. Beginning with methods to control the false discovery rate (FDR), the volume continues with chapters devoted to software suites for constructing quantitation data tables, missing value related issues, differential analysis software, and more. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and implementation advice that leads to successful results. Authoritative and practical, Statistical Analysis of Proteomic Data: Methods and Tools serves as an ideal guide for proteomics researchers looking to extract the best of their data with state-of-the art tools while also deepening their understanding of data analysis.

This book covers liquid chromatography, gas chromatography and capillary electrophoresis, the three main separation techniques lately available, applied to key omic sciences, such as genomics, proteomics, metabolomics and foodomics. The fundamentals of each technique are not covered herein. Instead, the recent advances in such techniques are presented focusing on the application to omics analyses and unique aspects in each case. This volume intends to offer wide ranging options available to researchers on omics sciences, and how to integrate them in order to achieve the comprehension of a biological system as a whole. Omic sciences have been of ultimate importance to comprehend the complex biochemical reactions and related events that occurs upon a biological system. The classical central dogma of molecular biology, which states that genetic information flows unidirectionally from DNA to RNA and then to proteins, has been gradually replaced by the systems biology approach. This book presents a multidisciplinary approach that explains the biological system as a whole, where the entire organism is influenced by a variety of internal events as well as by the environment, showing that each level of the biological information flux may influence the previous or the subsequent one.

This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics. Chapter 16 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Proteomic and Metabolomic Approaches to Biomarker Discovery, Second Edition covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution. The book describes methods and presents a standard operating procedure for sample selection, preparation and storage, as well as data analysis and modeling. This new standard effectively eliminates the differing methodologies used in studies and creates a unified approach. Readers will learn the advantages and disadvantages of the various techniques discussed, as well as potential difficulties inherent to all steps in the biomarker discovery process. This second edition has been fully updated and revised to address recent advances in MS and NMR instrumentation, high-field NMR, proteomics and metabolomics for biomarker validation, clinical assays of biomarkers and clinical MS and NMR, identifying microRNAs and autoantibodies as biomarkers, MRM-MS assay development, top-down MS, glycosylation-based serum biomarkers, cell surface proteins in biomarker discovery, lipodomics for cancer biomarker discovery, and strategies to design studies to identify predictive biomarkers in cancer research. Addresses the full range of proteomic and metabolomic methods and technologies used for biomarker discovery and validation Covers all steps involved in biomarker discovery, from study design to study execution Serves as a vital resource for biochemists, biologists, analytical chemists, bioanalytical chemists, clinical and medical technicians, researchers in pharmaceuticals and graduate students