Data

Roseworthy 2014 Field trial phenotype data and matching 17K+ genotype data.

Adelaide University
Taylor, Julian ; Fruzangohar, Mario ; Walter, James
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25909/23949333.v1&rft.title=Roseworthy 2014 Field trial phenotype data and matching 17K+ genotype data.&rft.identifier=10.25909/23949333.v1&rft.publisher=Adelaide University&rft.description=Large scale data set from Australian Grains Technologies (AGT) containing wheat yield phenotype and matching genotypic marker set. This data is synonymous with the yield data used in the publication:Norman, A., Taylor, J., Tanaka, E., Telfer, P., Edwards, J., Martinant, J.-P., et al. (2017) Increased genomic prediction accuracy in wheat breeding using a large Australian panel. Theoretical and Applied Genetics, 130, 1–13. Field trial phenotype data columns:10,375 breeding lines.Grain yield Best Linear Unbiased Predictors (BLUPs) obtained from a spatial adjustment of original field trial with Genotype as random effects.Grain yield deregressed BLUPs based on the de-regression method of Garrick et al (2009).Adjusted grain yield consisting of grain yield de-regressed BLUPs with site mean added Genotype data consists of:10,375 rows named by the genotypes.17,114 columns named by the markers.Allele encodings are (AA, AB, BB) = (1, 0, -1).Imputed alleles were calculated using the nearest neighbour method of Rutkowski et al (2013). &rft.creator=Taylor, Julian &rft.creator=Fruzangohar, Mario &rft.creator=Walter, James &rft.edition=1&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_subject=Genomics&rft_subject=Field trial data&rft_subject=Genomic prediction&rft_subject=marker data&rft_subject=yield phenotyping&rft.type=dataset&rft.language=English Access the data

Full description

Large scale data set from Australian Grains Technologies (AGT) containing wheat yield phenotype and matching genotypic marker set. This data is synonymous with the yield data used in the publication:

Norman, A., Taylor, J., Tanaka, E., Telfer, P., Edwards, J., Martinant, J.-P., et al. (2017) Increased genomic prediction accuracy in wheat breeding using a large Australian panel. Theoretical and Applied Genetics, 130, 1–13.

Field trial phenotype data columns:

  • 10,375 breeding lines.
  • Grain yield Best Linear Unbiased Predictors (BLUPs) obtained from a spatial adjustment of original field trial with Genotype as random effects.
  • Grain yield deregressed BLUPs based on the de-regression method of Garrick et al (2009).
  • Adjusted grain yield consisting of grain yield de-regressed BLUPs with site mean added

Genotype data consists of:

  • 10,375 rows named by the genotypes.
  • 17,114 columns named by the markers.
  • Allele encodings are (AA, AB, BB) = (1, 0, -1).
  • Imputed alleles were calculated using the nearest neighbour method of Rutkowski et al (2013).

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Identifiers
ACN 633 798 857