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statgenHTP

statgenHTP is developed as an easy-to-use package for analyzing data coming from high throughput phenotyping (HTP) platform experiments. The package provides many options for plotting and exporting the results of the analyses. It was developed within the EPPN2020 project to meet the needs for automated analyses of HTP data.

Installation

Install from CRAN:

install.packages("statgenHTP")

Install latest development version from GitHub (requires remotes package):

remotes::install_github("Biometris/statgenHTP", ref = "develop", dependencies = TRUE)

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Version

Install

install.packages('statgenHTP')

Monthly Downloads

295

Version

1.0.7

License

GPL

Issues

Pull Requests

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Repository

https://github.com/Biometris/statgenHTP/

Homepage

https://biometris.github.io/statgenHTP/index.html

Maintainer

Bart-Jan van Rossum

Last Published

October 14th, 2024

Functions in statgenHTP (1.0.7)

as.data.frame.TP

Coerce TP object to data.frame

Greenhouse data for a maize experiment in the PhenoArch platform.

createTimePoints

Create an object of class TP

Count valid observations per plotId for a given trait

Extract predicted genotypic values

Extract corrected phenotypic values

Extract effective dimensions

Extract heritabilities

Growth chamber data for an Arabidopsis experiment in the Phenovator platform.

noCorrectedRoot

Root data corrected for outliers for single observations.

Plot the results of a fitted spline.

estimateSplineParameters

Extract estimates from fitted splines.

Fit P-Spline Hierarchical Curve Data Models

spatCorrectedArch

Maize data corrected for spatial trends.

detectSingleOut

Detect outliers for single observations

Plot function for class TP

Summary function for TP objects

Detect outliers for series of observations

Fit spatial models per time point

Plot function for class psHDM

Plot outliers for series of observations

spatCorrectedVator

Arabidopsis data corrected for spatial trends.

detectSingleOutMaize

detectSingleOutMaize

Extract time points

Plot outliers for single observations

Plot function for class fitMod

Extract variances

Maize data, genotypic predictions.

statgenHTP-package

statgenHTP: High Throughput Phenotyping (HTP) Data Analysis

Predict the P-Splines Hierarchical Curve Data Model

Plot the results of estimated spline parameters.

Replace outliers for series of observations by NA

removeSingleOut

Replace outliers for single observations by NA

removeTimePoints

Remove time points from an object of class TP

Summary function for fitMod objects

Count valid observations per time point for a given trait

Greenhouse data for an experiment in the RootPhAir platform.