Description Usage Arguments Author(s) See Also Examples
View source: R/plot.DEresults.R
Given a model contained in a DEresults
object, plot.DEresults
plots the fit of the model on the expression data for a specified gene/probe.
1 2 3 |
x |
An object of type |
covariate |
The covariate we wish to plot against the expression level data. |
geneNumber |
The index of the gene whose expression data should be plotted on the y-axis. |
plmDEobject |
An object of type |
loess |
Should a loess fit on the covariate and actual expression level data be plotted? |
legend |
Should a legend be plotted? |
legend.coor |
the coordinates of the legend. See |
... |
parameters to be passed to plot |
Jonas Mueller
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## create an object of type \code{plmDE} containing disease with "control"
## and "disease" groups with measures of weight and severity. Then fit model:
ExpressionData = as.data.frame(matrix(abs(rnorm(10000, 1, 1.5)), ncol = 100))
names(ExpressionData) = sapply(1:100, function(x) paste("Sample", x))
Genes = sapply(1:100, function(x) paste("Gene", x))
DataInfo = data.frame(sample = names(ExpressionData), group = c(rep("Control", 50),
rep("Diseased", 50)), weight = abs(rnorm(100, 50, 20)), severity = c(rep(0, 50),
abs(rnorm(50, 100, 20))))
plmDEobject = plmDEmodel(Genes, ExpressionData, DataInfo)
model = fitGAPLM(plmDEobject, continuousCovariates.fullModel = c("weight", "severity"),
compareToReducedModel = TRUE, indicators.reducedModel = NULL,
continuousCovariates.reducedModel = "weight")
plot(model, "weight", 6, plmDEobject)
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