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Last data update: 2014.03.03

R: Method "PhenTestResult"

PhenTestResult

R Documentation

Method "PhenTestResult"

Description

Creates PhenTestResult object based on test results or model building results. Internal function for the package. Not build for users to directly call.

Usage

    PhenTestResult(model.output=NULL, model.dataset=NULL,
            depVariable=NULL, 
            refGenotype=NULL,
            equation="withWeight", 
            method="MM", model.effect.batch=NULL, 
            model.effect.variance=NULL,model.effect.sex=NULL, 
            model.effect.interaction=NULL, model.output.interaction=NULL, 
            model.effect.weight=NULL, numberSexes=NULL,pThreshold=0.05, 
            model.formula.null=NULL,model.formula.genotype=NULL, 
            model.output.genotype.nulltest.pVal=NULL, 
            model.output.quality=NULL,model.output.summary=NULL,
            model.output.averageRefGenotype = NULL,
            model.output.percentageChanges = NULL)

Arguments

`model.output`	representing the model fit gls object or lme object
`model.dataset`	dataset used for modeling
`depVariable`	depending variable in the model
`refGenotype`	reference genotype in the model
`equation`	possible values: "withWeight" to include weight effect into model, "withoutWeight" to exclude weight effect from the model
`method`	possible values: "MM" to work with Mixed Model framework, "FE" to work with Fisher Exact Test framework
`model.effect.batch`	Result of the test for batch effect significance
`model.effect.variance`	Result of the test for residual variance effect
`model.effect.sex`	Result of the test for sex effect significance
`model.effect.weight`	Result of the test for weight effect significance
`model.effect.interaction`	Result of the test for genotype by sex interaction significance
`model.output.interaction`	Interaction test result: p-value
`numberSexes`	number of possible sex values in the dataset
`pThreshold`	p-value threshold used to evaluate the effect significance, default value 0.05
`model.formula.null`	formula for the model without genotype effect
`model.formula.genotype`	formula for the model with genotype effect
`model.output.genotype.nulltest.pVal`	Genotype test results: p-value
`model.output.quality`	vector that contains diagnostic test output for mixed model quality of fit
`model.output.summary`	named vector that contains summary of the model output
`model.output.averageRefGenotype`	named vector that contains mean values calculated for reference genotype records
`model.output.percentageChanges`	named vector that contains percentage changes values per sex

Value

Returns an instance of the PhenTestResult class.

Author(s)

Natalja Kurbatova, Natasha Karp, Jeremy Mason

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

    file <- system.file("extdata", "test1.csv", package="PhenStat")
    test <- PhenList(dataset=read.csv(file),
            testGenotype="Sparc/Sparc")
    # "testDataset" function calls "PhenTestResult" function internally
    result <- testDataset(test,
            equation="withoutWeight",
            depVariable="Lean.Mass")
    class(result)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(PhenStat)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/PhenStat/PhenTestResult.Rd_%03d_medium.png", width=480, height=480)
> ### Name: PhenTestResult
> ### Title: Method "PhenTestResult"
> ### Aliases: PhenTestResult
> 
> ### ** Examples
> 
>     file <- system.file("extdata", "test1.csv", package="PhenStat")
>     test <- PhenList(dataset=read.csv(file),
+             testGenotype="Sparc/Sparc")
Warning:
Dataset's column 'Assay.Date' has been renamed to 'Batch' and will be used for the batch effect modelling.

Information:
Dataset's 'Genotype' column has following values: '+/+', 'Sparc/Sparc'

Information:
Dataset's 'Sex' column has following value(s): 'Female', 'Male'

>     # "testDataset" function calls "PhenTestResult" function internally
>     result <- testDataset(test,
+             equation="withoutWeight",
+             depVariable="Lean.Mass")
Information:
Dependent variable: 'Lean.Mass'.

Information:
Perform all MM framework stages: startModel and finalModel.

Information:
Method: Mixed Model framework.

Information:
Equation: 'withoutWeight'.

Information:
Calculated values for model effects are: keepBatch=TRUE, keepEqualVariance=TRUE, keepWeight=FALSE, keepSex=TRUE, keepInteraction=FALSE.

>     class(result)
[1] "PhenTestResult"
attr(,"package")
[1] "PhenStat"
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>