| Chapter title |
Preprocessing and Pretreatment of Metabolomics Data for Statistical Analysis
|
|---|---|
| Chapter number | 6 |
| Book title |
Metabolomics: From Fundamentals to Clinical Applications
|
| Published in |
Advances in experimental medicine and biology, January 2017
|
| DOI | 10.1007/978-3-319-47656-8_6 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-947655-1, 978-3-31-947656-8
|
| Authors |
Ibrahim Karaman |
| Editors |
Alessandra Sussulini |
| Abstract |
From data acquisition to statistical analysis, metabolomics data need to undergo several processing steps, which are crucial for the data quality and interpretation of the results. In this chapter, methods for preprocessing, normalization, and pretreatment of metabolomics data generated from nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are presented and discussed. Preprocessing is reported for both NMR and MS analysis. The challenges in preprocessing such complex data are highlighted. Subsequently, normalization methods such as total area normalization, probabilistic quotient normalization, and quantile normalization are explained. Finally, several scaling and data transformation methods are discussed for metabolomics data pretreatment, which is an important step prior to statistical analysis. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 100 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 18% |
| Student > Master | 15 | 15% |
| Researcher | 11 | 11% |
| Student > Bachelor | 8 | 8% |
| Student > Doctoral Student | 7 | 7% |
| Other | 15 | 15% |
| Unknown | 26 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 21 | 21% |
| Chemistry | 18 | 18% |
| Agricultural and Biological Sciences | 9 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 5 | 5% |
| Unspecified | 4 | 4% |
| Other | 13 | 13% |
| Unknown | 30 | 30% |