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Phenotype

Remove Outliers from Phenotypic Data and Performs the Best Linear Unbiased Prediction

Installation

devtools::install_github("biozhp/Phenotype")

Usage

Remove outliers from phenotypic data

data("wheatph")
inlier <- outlier(x = wheatph, col = 5, fold = 1.5)

Calculate statistical indicators of phenotypic data

data("wheatph")
inlier <- outlier(x = wheatph, col = 5, fold = 1.5)
stat_out <- stat(x = inlier, col = 2)

Histogram drawing

data("wheatph")
inlier <- outlier(x = wheatph, col = 5, fold = 1.5)
stat_out <- stat(x = inlier, col = 2)
histplot(x = stat_out$mean)

Performs the Best Linear Unbiased Prediction (BLUP)

data("wheatph")
blup_out <- blup(x = wheatph, fold = 1.5)

Contact

For any bugs/issues/suggestions, please send emails to: Peng Zhao pengzhao@nwafu.edu.cn.

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Version

Install

install.packages('Phenotype')

Monthly Downloads

220

Version

0.1.0

License

Artistic-2.0

Issues

Pull Requests

Stars

Forks

Maintainer

Peng Zhao

Last Published

August 6th, 2020

Functions in Phenotype (0.1.0)

wheatds

Stripe rust disease severity (leaf areas infected, DS) of the wheat RIL population
outlier

outlier
stat

stat
histplot

histplot
blup

blup