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Statistical Analysis in Proteomics

  • Book
  • © 2016

Overview

Editors:
  1. Klaus Jung

    1. Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany

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  • Includes cutting-edge methods for the study of the statistical analysis of proteomics
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts

Part of the book series: Methods in Molecular Biology (MIMB, volume 1362)

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Table of contents (19 protocols)

  1. Front Matter

    Pages i-x
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  2. Proteomics, Study Design, and Data Processing

    1. Front Matter

      Pages 1-1
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    2. Introduction to Proteomics Technologies

      • Christof Lenz, Hassan Dihazi
      Pages 3-27

    3. Topics in Study Design and Analysis for Multistage Clinical Proteomics Studies

      • Irene Sui Lan Zeng
      Pages 29-61

    4. Preprocessing and Analysis of LC-MS-Based Proteomic Data

      • Tsung-Heng Tsai, Minkun Wang, Habtom W. Ressom
      Pages 63-76

    5. Normalization of Reverse Phase Protein Microarray Data: Choosing the Best Normalization Analyte

      • Antonella Chiechi
      Pages 77-89

    6. Outlier Detection for Mass Spectrometric Data

      • HyungJun Cho, Soo-Heang Eo
      Pages 91-102

  3. Group Comparisons

    1. Front Matter

      Pages 103-103
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    2. Visualization and Differential Analysis of Protein Expression Data Using R

      • Tomé S. Silva, Nadège Richard
      Pages 105-118

    3. False Discovery Rate Estimation in Proteomics

      • Suruchi Aggarwal, Amit Kumar Yadav
      Pages 119-128

    4. A Nonparametric Bayesian Model for Nested Clustering

      • Juhee Lee, Peter Müller, Yitan Zhu, Yuan Ji
      Pages 129-141

    5. Set-Based Test Procedures for the Functional Analysis of Protein Lists from Differential Analysis

      • Jochen Kruppa, Klaus Jung
      Pages 143-156

  4. Classification Methods

    1. Front Matter

      Pages 157-157
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    2. Classification of Samples with Order-Restricted Discriminant Rules

      • David Conde, Miguel A. Fernández, Bonifacio Salvador, Cristina Rueda
      Pages 159-174

    3. Application of Discriminant Analysis and Cross-Validation on Proteomics Data

      • Julia Kuligowski, David Pérez-Guaita, Guillermo Quintás
      Pages 175-184

    4. Protein Sequence Analysis by Proximities

      • Frank-Michael Schleif
      Pages 185-195

  6. Special Topics

    1. Front Matter

      Pages 225-225
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Keywords

About this book

This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different ‘omics’ fields, methods for analyzing data from proteomics experiments need their own specific adaptations. To satisfy that need, Statistical Analysis in Proteomics focuses on the planning of proteomics experiments, the preprocessing and analysis of the data, the integration of proteomics data with other high-throughput data, as well as some special topics. Written for the highly successful Methods in Molecular Biology series, the chapters contain the kind of detail and expert implementation advice that makes for a smooth transition to the laboratory.

Practical and authoritative, Statistical Analysis in Proteomics serves as an ideal reference for statisticians involved in the planning and analysis of proteomics experiments, beginners as well as advanced researchers, and also for biologists, biochemists, and medical researchers who want to learn more about the statistical opportunities in the analysis of proteomics data.

Editors and Affiliations

  • Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany

    Klaus Jung

Bibliographic Information

  • Book Title: Statistical Analysis in Proteomics

  • Editors: Klaus Jung

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-3106-4

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media New York 2016

  • Hardcover ISBN: 978-1-4939-3105-7Published: 10 November 2015

  • Softcover ISBN: 978-1-4939-7987-5Published: 27 March 2019

  • eBook ISBN: 978-1-4939-3106-4Published: 30 October 2015

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 1

  • Number of Pages: X, 313

  • Number of Illustrations: 27 b/w illustrations, 58 illustrations in colour

  • Topics: Protein Science

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