dimension_reduction-HierarchicalPartition-method {cola} | R Documentation

## Visualize columns after dimension reduction

### Description

Visualize columns after dimension reduction

### Usage

    ## S4 method for signature 'HierarchicalPartition'
    dimension_reduction(object,
        depth = max_depth(object), parent_node,
        top_n = NULL, method = c("PCA", "MDS", "t-SNE", "UMAP"),
        silhouette_cutoff = 0.5, scale_rows = TRUE)

### Arguments

`object` | A `HierarchicalPartition-class` object.
`depth` | Depth of the hierarchy.
`top_n` | Top n rows to use. By default it uses all rows in the original matrix.
`parent_node` | Parent node. If it is set, the function call is identical to `dimension_reduction(object[parent_node])`
`method` | Which method to reduce the dimension of the data. `MDS` uses `cmdscale`, `PCA` uses `prcomp`. `t-SNE` uses `Rtsne`. `UMAP` uses `umap`.
`silhouette_cutoff` | Cutoff of silhouette score. Data points with values less than it will be mapped to small points.
`scale_rows` | Whether perform scaling on matrix rows.

### Details

The class IDs are extract at `depth`.

### Value

No value is returned.

### Author(s)

Zuguang Gu <z.gu@dkfz.de>

### Examples

    data(cola_rh)
    dimension_reduction(cola_rh)
    dimension_reduction(cola_rh, parent_node = "00")

[Package cola version 1.0.1 Index]