vis.immunr_mds: PCA / MDS / tSNE visualisation (mainly overlap / gene usage)

In immunomind/immunarch: Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires

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()

immunomind/immunarch documentation built on March 20, 2024, 12:01 p.m.