Functional QTL mapping and genomic prediction of 3D height in wheat measured using a robotic field phenotyping platform

Published: 16 Jul 2019 | Version 2 | DOI: 10.17632/pkxpkw6j43.2
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Description of this data

We provided the raw phenotypic data (FA_data_raw.RData), and individual-TP BLUPs, B-spline bases, and the first functional PCs from the 5, 10, and 26 TPs (phenotypic_traits.RData). The rqtl package input files for scenarios R1, R5, and R9 are also provided (CSP_ph17_5t_R1, CSP_ph17_10t_R5, and CSP_ph17_R9). The additive genomic relationship matrix is available as VanRaden_matrixCSP.RData. The codes provided are (1) factor analytic model, (2) smoothing and dimensionality reduction, QTL scanning using (3) individual-TP and (4) functional mapping, (5) power simulations, genomic prediction (6) with and (7) without including covariates as fixed effects.

Experiment data files

Latest version

  • Version 2

    2019-07-16

    Published: 2019-07-16

    DOI: 10.17632/pkxpkw6j43.2

    Cite this dataset

    Hottis Lyra, Danilo (2019), “Functional QTL mapping and genomic prediction of 3D height in wheat measured using a robotic field phenotyping platform”, Mendeley Data, v2 http://dx.doi.org/10.17632/pkxpkw6j43.2

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Institutions

Rothamsted Research

Categories

QTL Mapping, Genomic Selection, Phenotyping, Time Series, Smoothing Curve

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CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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