Package: statgenHTP 1.0.7

Bart-Jan van Rossum

statgenHTP: High Throughput Phenotyping (HTP) Data Analysis

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/>).

Authors:Emilie J Millet [aut], Maria Xose Rodriguez Alvarez [aut], Diana Marcela Perez Valencia [aut], Isabelle Sanchez [aut], Nadine Hilgert [aut], Bart-Jan van Rossum [aut, cre], Fred van Eeuwijk [aut], Martin Boer [aut]

statgenHTP_1.0.7.tar.gz
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statgenHTP_1.0.7.tgz(r-4.4-any)statgenHTP_1.0.7.tgz(r-4.3-any)
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statgenHTP.pdf |statgenHTP.html✨
statgenHTP/json (API)
NEWS

# Install 'statgenHTP' in R:
install.packages('statgenHTP', repos = c('https://biometris.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/biometris/statgenhtp/issues

Datasets:
  • PhenoarchDat1 - Greenhouse data for a maize experiment in the PhenoArch platform.
  • PhenovatorDat1 - Growth chamber data for an Arabidopsis experiment in the Phenovator platform.
  • RootDat1 - Greenhouse data for an experiment in the RootPhAir platform.
  • noCorrectedRoot - Root data corrected for outliers for single observations.
  • spatCorrectedArch - Maize data corrected for spatial trends.
  • spatCorrectedVator - Arabidopsis data corrected for spatial trends.
  • spatPredArch - Maize data, genotypic predictions.

On CRAN:

geneticshigh-troughput-phenotyping

5.31 score 4 stars 17 scripts 481 downloads 19 exports 140 dependencies

Last updated 1 months agofrom:634b441aaa. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 13 2024
R-4.5-winOKNov 13 2024
R-4.5-linuxOKNov 13 2024
R-4.4-winNOTENov 13 2024
R-4.4-macNOTENov 13 2024
R-4.3-winNOTENov 13 2024
R-4.3-macNOTENov 13 2024

Exports:countValidcountValidPlotcreateTimePointsdetectSerieOutdetectSingleOutdetectSingleOutMaizeestimateSplineParametersfitModelsfitSplinefitSplineHDMgetCorrectedgetEffDimsgetGenoPredgetHeritgetTimePointsgetVarremoveSerieOutremoveSingleOutremoveTimePoints

Dependencies:abindagridatanimationbackportsbase64encbootbroombslibcachemcarcarDataclassclassIntcliclustercolorspacecorrplotcowplotcpp11crosstalkcurldata.tableDBIdendextendDerivdigestdoBydotCall64dplyrDTe1071ellipseemmeansestimabilityevaluatefactoextraFactoMineRfansifarverfastmapfieldsflashClustfontawesomeFormulafsgenericsggforceggnewscaleggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleapslifecyclelme4LMMsolverlocfitlubridatemagickmagrittrmapsMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpolyclippolynompromisesproxypurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreshape2rlangrmarkdownrstatixs2sassscalesscatterplot3dsfspamSparseMSpATSstringistringrsurvivalsystemfontstibbletidyrtidyselecttimechangetinytextweenrunitsutf8vctrsviridisviridisLitewithrwkxfunyaml

statgenHTP: A short overview

Emilie Millet, Diana M. Pérez-Valencia, Bart-Jan van Rossum

Rendered fromOverview_HTP.Rmdusingknitr::rmarkdownon Nov 13 2024.

Last update: 2022-12-13
Started: 2021-03-02

Readme and manuals

Help Manual

Help pageTopics
Coerce TP object to data.frameas.data.frame.TP
Count valid observations per time point for a given traitcountValid
Count valid observations per plotId for a given traitcountValidPlot
Create an object of class TPcreateTimePoints
Detect outliers for series of observationsdetectSerieOut
Detect outliers for single observationsdetectSingleOut
detectSingleOutMaizedetectSingleOutMaize
Extract estimates from fitted splines.estimateSplineParameters
Fit spatial models per time pointfitModels
Fit SplinesfitSpline
Fit P-Spline Hierarchical Curve Data ModelsfitSplineHDM
Extract corrected phenotypic valuesgetCorrected
Extract effective dimensionsgetEffDims
Extract predicted genotypic valuesgetGenoPred
Extract heritabilitiesgetHerit
Extract time pointsgetTimePoints
Extract variancesgetVar
Root data corrected for outliers for single observations.noCorrectedRoot
Greenhouse data for a maize experiment in the PhenoArch platform.PhenoarchDat1
Growth chamber data for an Arabidopsis experiment in the Phenovator platform.PhenovatorDat1
Plot function for class fitModplot.fitMod
Plot the results of a fitted spline.plot.HTPSpline
Plot function for class psHDMplot.psHDM
Plot outliers for series of observationsplot.serieOut
Plot outliers for single observationsplot.singleOut
Plot the results of estimated spline parameters.plot.splineEst
Plot function for class TPplot.TP
Predict the P-Splines Hierarchical Curve Data Modelpredict.psHDM
Replace outliers for series of observations by NAremoveSerieOut
Replace outliers for single observations by NAremoveSingleOut
Remove time points from an object of class TPremoveTimePoints
Greenhouse data for an experiment in the RootPhAir platform.RootDat1
Maize data corrected for spatial trends.spatCorrectedArch
Arabidopsis data corrected for spatial trends.spatCorrectedVator
Maize data, genotypic predictions.spatPredArch
Summary function for fitMod objectssummary.fitMod
Summary function for TP objectssummary.TP