R: Dimensionality reduction

immunr_pca {immunarch} | R Documentation

## Dimensionality reduction

### Description

Collect a set of principal variables, reducing the number of not important variables to analyse. Dimensionality reduction makes data analysis algorithms work faster and sometimes more accurate, since it also reduces noise in the data. Currently available methods are:

- `immunr_pca` performs PCA (Principal Component Analysis) using prcomp;

- `immunr_mds` performs MDS (Multi-Dimensional Scaling) using isoMDS;

- `immunr_tsne` performs tSNE (t-Distributed Stochastic Neighbour Embedding) using Rtsne.

### Usage

    immunr_pca(.data, .scale = default_scale_fun, .raw = TRUE, .orig = FALSE, .dist = FALSE)

    immunr_mds(.data, .scale = default_scale_fun, .raw = TRUE, .orig = FALSE, .dist = TRUE)

    immunr_tsne(.data, .perp = 1, .dist = TRUE, ...)

### Arguments

`.data` | A matrix or a data frame with features, distance matrix or output from repOverlapAnalysis or geneUsageAnalysis functions.
`.scale` | A function to apply to your data before passing it to any of dimensionality reduction algorithms. There is no scaling by default.
`.raw` | If TRUE then return non-processed output from dimensionality reduction algorithms. Pass FALSE if you want to visualise results.
`.orig` | If TRUE then return the original result from algorithms. Pass FALSE if you want to visualise results.
`.dist` | If TRUE then assume ".data" is a distance matrix.
`.perp` | The perplexity parameter for Rtsne. Sepcifies the number of neighbours each data point must have in the resulting plot.
`...` | Other parameters passed to Rtsne.

### Value

`immunr_pca` - an output from prcomp.

`immunr_mds` - an output from isoMDS.

`immunr_tsne` - an output from Rtsne.

### See Also

vis.immunr_pca for visualisations.

### Examples

    data(immdata)
    gu <- geneUsage(immdata$data)
    gu[is.na(gu)] <- 0
    gu <- t(as.matrix(gu[, -1]))
    immunr_pca(gu)
    immunr_mds(dist(gu))
    immunr_tsne(dist(gu))

[Package immunarch version 0.6.7 Index]