finalTFModel: Method "finalTFModel"

Description

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.

Usage

finalTFModel(phenTestResult, outputMessages = TRUE)

Arguments

phenTestResult

instance of the PhenTestResult class that comes from the function testDataset; mandatory argument

outputMessages

flag: "FALSE" value to suppress output messages; "TRUE" value to show output messages; default value TRUE

Value

Returns results stored in instance of the PhenTestResult class

References

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.

Examples

Run this code

    file <- system.file("extdata", "test7_TFE.csv", package="PhenStat")
    test <- PhenList(dataset=read.csv(file),
                     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 <- 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  <- testDataset(test_TF,
                           depVariable="Cholesterol",
                           callAll=FALSE,
                           method="TF")
    # print out formula that has been created
    analysisResults(result)$model.formula.genotype
    # print out batch effect's significance 
    analysisResults(result)$model.effect.batch
    result <- finalTFModel(result)