To clean or not to clean phenotypic datasets for outlier plants in genetic analyses?
© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology.
| Veröffentlicht in: | Journal of experimental botany. - 1985. - 70(2019), 15 vom: 07. Aug., Seite 3693-3698 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2019
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| Zugriff auf das übergeordnete Werk: | Journal of experimental botany |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't Allele frequency genetic analysis outliers phenomics quantitative trait loci statistical analysis Plant Proteins |
| Zusammenfassung: | © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology. Based on case studies, we discuss the extent to which genome-wide association studies (GWAS) are affected by outlier plants, i.e. those deviating from the expected distribution on a multi-criteria basis. Using a raw dataset consisting of daily measurements of leaf area, biomass, and plant height for thousands of plants, we tested three different cleaning methods for their effects on genetic analyses. No-cleaning resulted in the highest number of dubious quantitative trait loci, especially at loci with highly unbalanced allelic frequencies. A trade-off was identified between the risk of false-positives (with no-cleaning and/or a low threshold for minor allele frequency) and the risk of missing interesting rare alleles. Cleaning can lower the risk of the latter by making it possible to choose a higher threshold in GWAS |
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| Beschreibung: | Date Completed 20.07.2020 Date Revised 20.07.2020 published: Print Citation Status MEDLINE |
| ISSN: | 1460-2431 |
| DOI: | 10.1093/jxb/erz191 |