plot_integrated_density_3D {OMICsPCA} | R Documentation

## Visualization of 3D Density of various groups on Principal components of multiple Assays

### Description

works similarly as "plot_density_3D" . See vignettes and man page of "plot_density_3D" for more details.

### Usage

    plot_integrated_density_3D(name, PC1 = 1, PC2 = 2, group,
    gridsize = 100, static = FALSE, groupinfo = NULL, ...)

### Arguments

`name` | Name of the integrated "PCA" object
`PC1, PC2` | Numbers corresponding to the principal components on which density is to be calculated
`group` | Names of a group
`gridsize` | A number used in kernel smoothing. default is 100
`static` | Logical if TRUE a static plot is generated. default = FALSE
`groupinfo` | same as integrate_variables()
`...` | additional arguments allowed to base function "persp" of package "graphics"

### Details

2D density is calculated using the "kde2d"" function from package "MASS"" which use kernel density estimation (KDE) to calculate density of 2D data. If the variance on either or both of the PCs are 0, the KDE can't be calculated.

### Value

Displays 3D density plots.

### Author(s)

Subhadeep Das <subhadeep1024@gmail.com>

### Examples

    exclude <- list(0,c(1,9))

    int_PCA <- integrate_pca(Assays = c("H2az",
    "H3k9ac"), name = multi_assay, mergetype = 2,
    exclude = exclude, groupinfo = groupinfo_ext,
    ,graph = FALSE)

    name = int_PCA$int_PCA

    plot_integrated_density_3D(name = name, PC1 = 1, PC2 = 2,
    group = c("WE","RE"), gridsize = 100, static = FALSE,
    groupinfo = groupinfo_ext)

[Package OMICsPCA version 1.10.0 Index]