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

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

## Documentation for package ‘DepecheR’ version 1.28.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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
neighSmooth | Euclidean neighbor smoothing
nUniqueNeighDons | How many donors are contained among the nearest neighbors?
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