cluster_plot {CellaRepertorium} | R Documentation

## Make a plot showing properties of the clustering

### Description

The number of elements per cluster and the average distance between the medoid and other elements are plotted.

### Usage

    cluster_plot(cdb, return_plotlist = FALSE)

### Arguments

`cdb` | A `fine_clustering` `ContigCellDB` object
`return_plotlist` | should a list of `ggplot2` plots be returned. If FALSE, a `cowplot` composite is retuned.

### Value

a `cowplot` composite or a list of plots.

### Examples

    library(dplyr)
    data(ccdb_ex)
    ccdb_ex_small = ccdb_ex
    ccdb_ex_small$cell_tbl = ccdb_ex_small$cell_tbl[1:200,]
    ccdb_ex_small = cdhit_ccdb(ccdb_ex_small,
    sequence_key = 'cdr3_nt', type = 'DNA', cluster_name = 'DNA97',
    identity = .965, min_length = 12, G = 1)
    ccdb_ex_small = fine_clustering(ccdb_ex_small, sequence_key = 'cdr3_nt', type = 'DNA')

    # Canonicalize with the medoid contig is probably what is most common
    ccdb_medoid = canonicalize_cluster(ccdb_ex_small)

    # But there are other possibilities.
    # To pass multiple "AND" filter arguments must use &
    ccdb_umi = canonicalize_cluster(ccdb_ex_small,
    contig_filter_args = chain == 'TRA' & length > 500, tie_break_keys = 'umis',
    contig_fields = c('chain', 'length'))
    ccdb_umi$cluster_tbl %>% dplyr::select(chain, length) %>% summary()
    cluster_plot(ccdb_ex_small)

[Package CellaRepertorium version 1.2.0 Index]