plot_cluster_factors {CellaRepertorium} | R Documentation

## Visualization of pairs of cluster factor

### Description

With `factors`, a pair of variables present in the `contig_tbl` and the `cluster_tbl`, generate and plot cross-tabs of the number of contigs, or its pearson residual.

### Usage

    plot_cluster_factors(
      ccdb,
      factors,
      type = c("heatmap", "network"),
      statistic = c("pearson", "contigs"),
      ncluster = 0,
      chaintype
    )

### Arguments

`ccdb` | A ContigCellDB object.
`factors` | `character` length 2 of fields present
`type` | Type of visualization, a heatmap or a node-edge network plot
`statistic` | Cluster characteristics visualized by pearson residuals or raw contig counts
`ncluster` | `integer`. Omit factors that occur less than `nclusters`. For clarity of visualization.
`chaintype` | Character in ccdb$contig_tbl$chain. If passed will subset contigs belonging to specified chain (IGH,IGK,IGL,TRA,TRB)

### Value

A ggraph object if type == 'network', and a ggplot object if type == 'heatmap'

### See Also

canonicalize_cluster to "roll-up" additional contig variables into the 'cluster_tbl“

### Examples

    library(ggraph)
    data(ccdb_ex)
    ccdb_germline_ex = cluster_germline(ccdb_ex, segment_keys = c('v_gene', 'j_gene', 'chain'),
    cluster_pk = 'segment_idx')
    ccdb_germline_ex = fine_clustering(ccdb_germline_ex, sequence_key = 'cdr3_nt', type = 'DNA')
    plot_cluster_factors(ccdb_germline_ex,factors = c('v_gene','j_gene'),
    statistic = 'pearson', type = 'network' ,ncluster = 10, chaintype = 'TRB')
    plot_cluster_factors(ccdb_germline_ex,factors = c('v_gene','j_gene'),
    statistic = 'contigs', type = 'heatmap')
    plot_cluster_factors(ccdb_germline_ex,factors = c('v_gene','j_gene'),
    statistic = 'contigs', type = 'network', ncluster = 10)

[Package CellaRepertorium version 1.4.0 Index]