R: Post-analysis of public clonotype statistics: PCA,...

repOverlapAnalysis {immunarch} | R Documentation

## Post-analysis of public clonotype statistics: PCA, clustering, etc.

### Description

The `repOverlapAnalysis` function contains advanced data analysis methods. You can use several clustering and dimensionality reduction techniques in order to investigate further the difference between repertoires provided.

To cluster a subset of similar data with `repOverlapAnalysis` you can perform hierarchical clustering, k-means or dbscan ('hclust', 'kmeans', 'dbscan' respectively).

To reduce dimensions, for example, to select features for subsequent analysis, you can execute the multidimensional scaling or t-sne algorithms ('mds' and 'tsne' respectively).

### Usage

    repOverlapAnalysis(
      .data,
      .method = ("hclust"),
      .scale = default_scale_fun,
      .raw = TRUE,
      .perp = 1,
      .theta = 0.1,
      .eps = 0.01,
      .k = 2
    )

### Arguments

`.data` | Any distance matrix between pairs of repertoires. You can also pass your output from `repOverlap`.
`.method` | A string that defines the type of analysis to perform.
`.scale` | A function to scale the data before passing it to the MDS algorithm.
`.raw` | A logical value. Pass TRUE if you want to receive raw output of clustering or dimensionality reduction function of choice. Pass FALSE if you want to receive processed output that can be subjected to visualisation with `vis` function.
`.perp` | A numerical value, t-SNE parameter, see `immunr_tsne`.
`.theta` | A numerical value, t-SNE parameter, see `immunr_tsne`.
`.eps` | A numerical value, DBscan epsylon parameter, see `immunr_dbscan`.
`.k` | The number of clusters to create, passed as `k` to hcut or as `centers` to kmeans.

### Value

Depends on the last element in the `.method` string. See immunr_tsne for more info.

### Examples

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

[Package immunarch version 0.6.5 Index]