instance of the PhenTestResult class; mandatory argument
graphingName
a character string defining the name to be used on the graph for the dependent variable; mandatory argument
outputMessages
flag: "FALSE" value to suppress output messages; "TRUE" value to show output messages; default value TRUE
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 ONE7(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.
See Also
PhenList
Examples
file <- system.file("extdata", "test1.csv", package="PhenStat")
test <- PhenList(dataset=read.csv(file),
testGenotype="Sparc/Sparc")
result <- testDataset(test,
depVariable="Lean.Mass")
# box plot for dataset with two sexes: males and females
boxplotSexGenotypeResult(result,
graphingName="BMC")
file <- system.file("extdata", "test4.csv", package="PhenStat")
test_1sex <- PhenList(dataset=read.csv(file),
testGenotype="Mysm1/+")
result_1sex <- testDataset(test_1sex,
depVariable="Lean.Mass")
# box plot for females only dataset
boxplotSexGenotypeResult(result_1sex,
graphingName="Lean Mass (g)")
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/boxplotSexGenotypeResult.Rd_%03d_medium.png", width=480, height=480)
> ### Name: boxplotSexGenotypeResult
> ### Title: Method "boxplotSexGenotypeResult"
> ### Aliases: boxplotSexGenotypeResult
>
> ### ** 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'
> result <- testDataset(test,
+ depVariable="Lean.Mass")
Information:
Dependent variable: 'Lean.Mass'.
Information:
Perform all MM framework stages: startModel and finalModel.
Information:
Method: Mixed Model framework.
Information:
Equation: 'withWeight'.
Information:
Calculated values for model effects are: keepBatch=TRUE, keepEqualVariance=FALSE, keepWeight=TRUE, keepSex=TRUE, keepInteraction=FALSE.
> # box plot for dataset with two sexes: males and females
> boxplotSexGenotypeResult(result,
+ graphingName="BMC")
>
> file <- system.file("extdata", "test4.csv", package="PhenStat")
> test_1sex <- PhenList(dataset=read.csv(file),
+ testGenotype="Mysm1/+")
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: '+/+', 'Mysm1/+'
Information:
Dataset's 'Sex' column has following value(s): 'Female'
> result_1sex <- testDataset(test_1sex,
+ depVariable="Lean.Mass")
Information:
Dependent variable: 'Lean.Mass'.
Information:
Perform all MM framework stages: startModel and finalModel.
Information:
Method: Mixed Model framework.
Information:
Equation: 'withWeight'.
Information:
Calculated values for model effects are: keepBatch=TRUE, keepEqualVariance=TRUE, keepWeight=TRUE, keepSex=FALSE, keepInteraction=FALSE.
> # box plot for females only dataset
> boxplotSexGenotypeResult(result_1sex,
+ graphingName="Lean Mass (g)")
>
>
>
>
>
> dev.off()
null device
1
>