Genomic Regression Workbench

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Documentation for package ‘GROAN’ version 1.3.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

addRegressor	Add an extra regressor to a Workbench
are.compatible	Check two GROAN.NoisyDataSet for dimension compatibility
createNoisyDataset	Noisy Data Set Constructor
createRunId	Generate a random run id
createWorkbench	Workbench constructor
getNoisyPhenotype	Generate an instance of noisy phenotypes
GROAN.AI	Example data for pea AI lines
GROAN.KI	Example data for pea KI lines
GROAN.pea.kinship	[DEPRECATED]
GROAN.pea.SNPs	[DEPRECATED]
GROAN.pea.yield	[DEPRECATED]
GROAN.run	Compare Genomic Regressors on a Noisy Dataset
measurePredictionPerformance	Measure Performance of a Prediction
ndcg	Function to calculate mean Normalized Discounted Cumulative Gain (NDCG)
noiseInjector.dummy	Noise Injector dummy function
noiseInjector.norm	Inject Normal Noise
noiseInjector.swapper	Swap phenotypes between samples
noiseInjector.unif	Inject Uniform Noise
phenoRegressor.BGLR	Regression using BGLR package
phenoregressor.BGLR.multikinships	Multi-matrix GBLUP using BGLR
phenoRegressor.dummy	Regression dummy function
phenoRegressor.RFR	Random Forest Regression using package randomForest
phenoRegressor.rrBLUP	SNP-BLUP or G-BLUP using rrBLUP package
phenoRegressor.SVR	Support Vector Regression using package e1071
plotResult	Plot results of a run
print.GROAN.NoisyDataset	Print a GROAN Noisy Dataset object
print.GROAN.Workbench	Print a GROAN Workbench object
summary.GROAN.NoisyDataset	Summary for GROAN Noisy Dataset object
summary.GROAN.Result	Summary of GROAN.Result