finalTFModel {PhenStat} | R Documentation |
This is an internal function run within TF framework. It completes the final stage of the TF framework, which builds the final model and estimates effects. As an internal function, it doesn't include extensive error testing of inputs. Please use cautiously if calling directly.
Works with PhenTestResult
object created by startTFModel
function.
The creation of TF final model is based on the significance of different fixed effects, depVariable and equation values
stored in PhenTestResult
object.
finalTFModel(phenTestResult, outputMessages = TRUE)
phenTestResult |
instance of the |
outputMessages |
flag: "FALSE" value to suppress output messages; "TRUE" value to show output messages; default value TRUE |
Returns results stored in instance of the PhenTestResult
class
Natalja Kurbatova, Natasha Karp, Jeremy Mason
Karp N, Melvin D, Sanger Mouse Genetics Project, Mott R (2012): Robust and Sensitive Analysis of Mouse Knockout Phenotypes. PLoS ONE 7(12): e52410. doi:10.1371/journal.pone.0052410
West B, Welch K, Galecki A (2007): Linear Mixed Models: A practical guide using statistical software New York: Chapman & Hall/CRC 353 p.
PhenTestResult
and testDataset
file <- system.file("extdata", "test7_TFE.csv", package="PhenStat") test <- PhenList(dataset=read.csv(file,na.strings = '-'), testGenotype="het", refGenotype = "WT", dataset.colname.sex="sex", dataset.colname.genotype="Genotype", dataset.values.female="f", dataset.values.male= "m", dataset.colname.weight="body.weight", dataset.colname.batch="Date_of_procedure_start") test_TF <- PhenStat:::TFDataset(test,depVariable="Cholesterol") # when "testDataset" function's argument "callAll" is set to FALSE # only "startTFModel" function is called - the first step of TFE framework result <- PhenStat:::testDataset(test_TF, depVariable="Cholesterol", callAll=FALSE, method="TF") # print out formula that has been created PhenStat:::analysisResults(result)$model.formula.genotype # print out batch effect's significance PhenStat:::analysisResults(result)$model.effect.batch result <- PhenStat:::finalTFModel(result)