boxplotSexGenotypeBatch: Method "boxplotSexGenotypeBatch"
In PhenStat: Statistical analysis of phenotypic data

Description Usage Arguments Value Author(s) References See Also Examples

NB! Function is deprecated, please use scatterplotSexGenotypeBatch function instead. Graph function for the phenotypic dataset. Creates a box plot split by sex, genotype and batch.

Note: the batches are not ordered with time but allow assessment of how the treatment groups lie relative to the normal control variation.

    boxplotSexGenotypeBatch(phenList,
							depVariable=NULL,
							graphingName=NULL,
							outputMessages=TRUE)

`phenList`	instance of the `PhenList` class; mandatory argument
`depVariable`	a character string defining the dependent variable of interest; 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

Empty.

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.

PhenList

    file <- system.file("extdata", "test1.csv", package="PhenStat")
    test <- PhenStat:::PhenList(dataset=read.csv(file,na.strings = '-'),
            testGenotype="Sparc/Sparc")
    # box plot for dataset with two sexes: males and females
    PhenStat:::boxplotSexGenotypeBatch(test,
            depVariable="Bone.Mineral.Content",
            graphingName="BMC" )

    file <- system.file("extdata", "test4.csv", package="PhenStat")
    test_1sex <- PhenStat:::PhenList(dataset=read.csv(file,na.strings = '-'),
            testGenotype="Mysm1/+")
    # box plot for females only dataset
    PhenStat:::boxplotSexGenotypeBatch(test_1sex,depVariable="Lean.Mass",
            graphingName="Lean Mass")