plot_landscape {microbiome} | R Documentation

## Landscape Plot

### Description

Wrapper for visualizing sample similarity landscape ie. sample density in various 2D projections.

### Usage

    plot_landscape(x, method = "PCoA", distance = "bray",
      transformation = "identity", col = NULL, main = NULL,
      x.ticks = 10, rounding = 0, add.points = TRUE, adjust = 1,
      size = 1, legend = FALSE, shading = TRUE)

### Arguments

`x` | `phyloseq-class` object or a data matrix (samples x features; eg. samples vs. OTUs). If the input x is a 2D matrix then it is plotted as is.
`method` | Ordination method, see phyloseq::plot_ordination; or "PCA", or "t-SNE" (from the Rtsne package)
`distance` | Ordination distance, see phyloseq::plot_ordination; for method = "PCA", only euclidean distance is implemented now.
`transformation` | Transformation applied on the input object x
`col` | Variable name to highlight samples (points) with colors
`main` | title text
`x.ticks` | Number of ticks on the X axis
`rounding` | Rounding for X axis tick values
`add.points` | Plot the data points as well
`adjust` | Kernel width adjustment
`size` | point size
`legend` | plot legend TRUE/FALSE
`shading` | Add shading in the background.

### Details

For consistent results, set random seet (set.seed) before function call. Note that the distance and transformation arguments may have a drastic effect on the outputs.

### Value

A `ggplot` plot object.

### Examples

    data(dietswap)

    # PCoA
    p <- plot_landscape(transform(dietswap, "compositional"),
       distance = "bray", method = "PCoA")

    p <- plot_landscape(dietswap, method = "t-SNE", distance = "bray",
           transformation = "compositional")

    # PCA
    p <- plot_landscape(dietswap, method = "PCA", transformation = "clr")

[Package microbiome version 1.8.0 Index]