cluster {CATALYST} | R Documentation

## FlowSOM clustering & ConsensusClusterPlus metaclustering

### Description

`cluster` will first group cells into `xdim`x`ydim` clusters using FlowSOM, and subsequently perform metaclustering with ConsensusClusterPlus into 2 through `maxK` clusters. In the returned `daFrame`, those antigens used for clustering will be labelled as '`type`' markers, and the remainder of antigens as '`state`' markers.

### Usage

    cluster(x, ...)

    ## S4 method for signature 'daFrame'
    cluster(x, cols_to_use, xdim = 10, ydim = 10,
      maxK = 20, verbose = TRUE, seed = 1)

### Arguments

`x` | a `daFrame`.
`...` | optional arguments.
`cols_to_use` | a character vector. Specifies which antigens to use for clustering.
`xdim, ydim` | numeric. Specify the grid size of the self-orginizing map. The default 10x10 grid will yield 100 clusters.
`maxK` | numeric. Specifies the maximum number of clusters to evaluate in the metaclustering. For `maxK = 20`, for example, metaclustering will be performed for 2 through 20 clusters.
`verbose` | logical. Should information on progress be reported?
`seed` | numeric. Sets random seed in `ConsensusClusterPlus()`.

### Details

The delta area represents the amount of extra cluster stability gained when clustering into k groups as compared to k-1 groups. It can be expected that high stability of clusters can be reached when clustering into the number of groups that best fits the data. The "natural" number of clusters present in the data should thus corresponds to the value of k where there is no longer a considerable increase in stability (pleateau onset).

### Value

The function will add information to the following slots of the input `daFrame` (and return it):

- `rowData`

  - `cluster_id`: each cell's cluster ID as inferred by `FlowSOM`. One of 1, ..., `xdim`x`ydim`.

- `colData`

  - `marker_class`: `"type"` or `"state"`. Specifies whether an antigen has been used for clustering or not, respectively.

- `metadata`

  - `SOM_codes`: a table with dimensions K x (# cell type markers), where K = `xdim` x `ydim`. Contains the SOM codes.

  - `cluster_codes`: a table with dimensions K x (`maxK` + 1). Contains the cluster codes for all metaclustering.

  - `delta_area`: a `ggplot` object. See above for details.

### Author(s)

Helena Lucia Crowell crowellh@student.ethz.ch

### References

Nowicka M, Krieg C, Weber LM et al. CyTOF workflow: Differential discovery in high-throughput high-dimensional cytometry datasets. F1000Research 2017, 6:748 (doi: 10.12688/f1000research.11622.1)

### Examples

    data(PBMC_fs, PBMC_panel, PBMC_md)
    re <- daFrame(PBMC_fs, PBMC_panel, PBMC_md)

    # specify antigens to use for clustering
    lineage <- c("CD3", "CD45", "CD4", "CD20", "CD33",
        "CD123", "CD14", "IgM", "HLA_DR", "CD7")
    (re <- cluster(re, cols_to_use=lineage))

[Package CATALYST version 1.4.2 Index]