High Throughput Phenotyping (HTP) Data Analysis
Coerce TP object to data.frame
Count valid observations per time point for a given trait
Extract heritabilities
Extract time points
Plot the results of estimated spline parameters.
Plot function for class TP
Predict the P-Splines Hierarchical Curve Data Model
Count valid observations per plotId for a given trait
Create an object of class TP
Detect outliers for series of observations
Detect outliers for single observations
detectSingleOutMaize
Extract estimates from fitted splines.
Fit spatial models per time point
Fit Splines
Fit P-Spline Hierarchical Curve Data Models
Extract corrected phenotypic values
Extract effective dimensions
Extract predicted genotypic values
Extract variances
Plot function for class fitMod
Plot the results of a fitted spline.
Plot function for class psHDM
Plot outliers for series of observations
Plot outliers for single observations
Replace outliers for series of observations by NA
Replace outliers for single observations by NA
Remove time points from an object of class TP
statgenHTP: High Throughput Phenotyping (HTP) Data Analysis
Summary function for fitMod objects
Summary function for TP objects
Phenotypic analysis of data coming from high throughput phenotyping (HTP) platforms, including different types of outlier detection, spatial analysis, and parameter estimation. The package is being developed within the EPPN2020 project (<https://eppn2020.plant-phenotyping.eu/>). Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://vsni.co.uk/software/asreml-r/>).
Useful links