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Phenotype: A Tool for Phenotypic Data Processing

Large-scale phenotypic data processing is essential in research. Researchers need to eliminate outliers from the data in order to obtain true and reliable results. Best linear unbiased prediction (BLUP) is a standard method for estimating random effects of a mixed model. This method can be used to process phenotypic data under different conditions and is widely used in animal and plant breeding. The 'Phenotype' can remove outliers from phenotypic data and performs the best linear unbiased prediction (BLUP), help researchers quickly complete phenotypic data analysis. H.P.Piepho. (2008) <doi:10.1007/s10681-007-9449-8>.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: lme4, tidyr
Published: 2020-08-06
DOI: 10.32614/CRAN.package.Phenotype
Author: Peng Zhao [aut, cre]
Maintainer: Peng Zhao <pengzhao at nwafu.edu.cn>
BugReports: https://github.com/biozhp/Phenotype/issues
License: Artistic-2.0
URL: https://github.com/biozhp/Phenotype
NeedsCompilation: no
Materials: README
CRAN checks: Phenotype results

Documentation:

Reference manual: Phenotype.pdf

Downloads:

Package source: Phenotype_0.1.0.tar.gz
Windows binaries: r-devel: Phenotype_0.1.0.zip, r-release: Phenotype_0.1.0.zip, r-oldrel: Phenotype_0.1.0.zip
macOS binaries: r-release (arm64): Phenotype_0.1.0.tgz, r-oldrel (arm64): Phenotype_0.1.0.tgz, r-release (x86_64): Phenotype_0.1.0.tgz, r-oldrel (x86_64): Phenotype_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.