Determination of essential phenotypic elements of clusters in high-dimensional entities

Documentation for package ‘DepecheR’ version 1.2.0

DepecheR-package	DepecheR: Determination of essential phenotypic elements of clusters in high-dimensional entities
dAllocate	Allocation of observations to pre-established cluster centers.
dColorPlot	Display third variable as color on a 2D plot
dColorVector	Create a vector of colors of the same length as the data
dContours	Create density contours for two-dimensional data.
dDensityPlot	Display density on 2D plot
depeche	Perform optimization and penalized K-means clustering
DepecheR	DepecheR: Determination of essential phenotypic elements of clusters in high-dimensional entities
dResidualPlot	Showing the residuals when subtracting the values from one group from another on a SNE plot
dScale	Scaling of a vector or a dataframe.
dSplsda	Sparse partial least squares discriminant analysis with paired and unpaired data
dViolins	Create violin plots for any variables of choise
dWilcox	Wilcoxon rank-sum or signed rank test comparison of subject groups in a dClust result
groupProbPlot	Define and plot group probabilities
microClust	This function is the core of the groupProbPlot. See the documentation there for details.
testData	A 14 color flow cytometry dataset for example execution and playing around
testDataDepeche	A depeche clustering of the testData set
testDataSNE	SNE of the testData set