Data from: Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement

Spindel JE, Begum H, Akdemir D, Collard B, Redoña E, Jannink J-L, McCouch S

Date Published: December 4, 2015

DOI: http://dx.doi.org/10.5061/dryad.vv28j

 

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Title IRRI MET 2011 2012 phenotype data all files
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Description This archive contains the raw multi-environment (MET) phenotype data used for the MET GS experiments reported in this publication. Each .csv file in the archive contains the data for a particular year, season, and site. See ReadMe file for description of columns.
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Download MET_2011_2012_pheno_data_all.zip (165.8 Kb)
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When using this data, please cite the original publication:

Spindel JE, Begum H, Akdemir D, Collard B, Redoña E, Jannink J-L, McCouch S (2016) Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement. Heredity 116: 395–408. http://dx.doi.org/10.1038/hdy.2015.113

Additionally, please cite the Dryad data package:

Spindel JE, Begum H, Akdemir D, Collard B, Redoña E, Jannink J-L, McCouch S (2016) Data from: Genome-wide prediction models that incorporate de novo GWAS are a powerful new tool for tropical rice improvement. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.vv28j
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