R: PCA / MDS / tSNE visualisation (mainly overlap / gene usage)

vis.immunr_mds {immunarch} | R Documentation

## PCA / MDS / tSNE visualisation (mainly overlap / gene usage)

### Description

PCA / MDS / tSNE visualisation (mainly overlap / gene usage)

### Usage

    ## S3 method for class 'immunr_mds'
    vis(
      .data,
      .by = NA,
      .meta = NA,
      .point = TRUE,
      .text = TRUE,
      .ellipse = TRUE,
      .point.size = 2,
      .text.size = 4,
      ...
    )

### Arguments

`.data` | Output from analysis functions such as geneUsageAnalysis or immunr_pca, immunr_mds or immunr_tsne.
`.by` | Pass NA if you want to plot samples without grouping. You can pass a character vector with one or several column names from ".meta" to group your data before plotting. In this case you should provide ".meta". You can pass a character vector that exactly matches the number of samples in your data, each value should correspond to a sample's property. It will be used to group data based on the values provided. Note that in this case you should pass NA to ".meta".
`.meta` | A metadata object. An R dataframe with sample names and their properties, such as age, serostatus or hla.
`.point` | Logical. If TRUE then plot points corresponding to objects.
`.text` | Logical. If TRUE then plot sample names.
`.ellipse` | Logical. If TRUE then plot ellipses around clusters of grouped samples.
`.point.size` | Numeric. A size of points to plot.
`.text.size` | Numeric. A size of sample names' labels.
`...` | Not used here.

### Details

Other visualisation methods:

- PCA - vis.immunr_pca

- MDS - vis.immunr_mds

- tSNE - vis.immunr_tsne

### Value

A ggplot2 object.

### Examples

    data(immdata)
    ov <- repOverlap(immdata$data)
    repOverlapAnalysis(ov, "mds") %>% vis()

[Package immunarch version 0.6.7 Index]