scatterplotSexGenotypeBatch {PhenStat} | R Documentation |
Graph function for the phenotypic dataset. Creates a scatterplot split by sex, genotype and batch. refGenotype data points are shown in black and the testGenotype data points are shown in red.
Note: the batches are not ordered with time but allow assessment of how the testGenotype data lie relative to the variation within the refGenotype data.
scatterplotSexGenotypeBatch( phenList, depVariable = NULL, graphingName = NULL, outputMessages = TRUE )
phenList |
instance of the |
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.
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:::scatterplotSexGenotypeBatch(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:::scatterplotSexGenotypeBatch(test_1sex,depVariable="Lean.Mass", graphingName="Lean Mass")