Regression-based modeling of complex plant traits based on metabolomics data
- Bridging metabolomics with plant phenotypic responses is challenging. Multivariate analyses account for the existing dependencies among metabolites, and regression models in particular capture such dependencies in search for association with a given trait. However, special care should be undertaken with metabolomics data. Here we propose a modeling workflow that considers all caveats imposed by such large data sets.
| Author details: | Francisco Anastacio de Abreu e LimaORCiDGND, Lydia Leifels, Zoran NikoloskiORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1007/978-1-4939-7819-9_23 |
| ISBN: | 978-1-4939-7819-9 |
| ISBN: | 978-1-4939-7818-2 |
| ISSN: | 1064-3745 |
| ISSN: | 1940-6029 |
| Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/29761449 |
| Title of parent work (English): | Plant Metabolomics |
| Publisher: | Humana Press Inc. |
| Place of publishing: | New York |
| Publication type: | Article |
| Language: | English |
| Date of first publication: | 2018/05/15 |
| Publication year: | 2018 |
| Release date: | 2022/03/18 |
| Tag: | Metabolomics; Modeling; Plants; Prediction; R programing language; R software packages; Regression; Trait |
| Volume: | 1778 |
| Number of pages: | 7 |
| First page: | 321 |
| Last Page: | 327 |
| Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie |
| DDC classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
| Peer review: | Referiert |
