R: One function to visualise them all

vis {immunarch} | R Documentation

## One function to visualise them all

### Description

Output from every function in immunarch can be visualised with a single function - `vis`. The `vis` automatically detects the type of the data and draws a proper visualisation. For example, output from the `repOverlap` function will be identified as repertoire overlap values and respective visualisation will be chosen without any additional arguments. See "Details" for the list of available visualisations.

### Usage

    vis(.data, ...)

### Arguments

`.data` | Pass the output from any immunarch analysis tool to `vis()`.
`...` | Any other arguments, see the "Details" section for specific visualisation functions.

### Details

List of available visualisations for different kinds of data.

Basic analysis:

- Exploratory analysis results (from repExplore) - see vis.immunr_exp_vol;

- Clonality statistics (from repClonality) - see vis.immunr_homeo.

Overlaps and public clonotypes:

- Overlaps (from repOverlap) using heatmaps, circos plots, polar area plots - see vis.immunr_ov_matrix;

- Overlap clustering (from repOverlapAnalysis) - see vis.immunr_hclust;

- Repertoire incremental overlaps (from repOverlap) - see vis.immunr_inc_overlap;

- Public repertoire abundance (from pubRep) - vis vis.immunr_public_repertoire.

Gene usage:

- Gene usage statistics (from geneUsage) using bar plots, box plots - see vis.immunr_gene_usage;

- Gene usage distances (from geneUsageAnalysis) using heatmaps, circos plots, polar area plots - see vis.immunr_ov_matrix;

- Gene usage clustering (from geneUsageAnalysis) - see vis.immunr_hclust.

Diversity estimation:

- Diversity estimations (from repDiversity) - see vis.immunr_chao1.

Advanced analysis:

- Repertoire dynamics (from trackClonotypes) - see vis.immunr_dynamics;

- Sequence logo plots of amino acid distributions (from kmer_profile) - see vis_seqlogo;

- Kmers distributions (from getKmers) - see vis.immunr_kmer_table;

- Mutation networks (from mutationNetwork) - Work In Progress on vis.immunr_mutation_network;

- CDR3 amino acid properties, e.g., biophysical (from cdrProp) - Work In Progress on vis.immunr_cdr_prop.

Additionaly, we provide a wrapper functions for visualisations of common data types:

- Any data frames or matrices using heatmaps - see vis_heatmap and vis_heatmap2;

- Any data frames or matrices using circos plots - see vis_circos.

### Value

A ggplot2, pheatmap or circlize object.

### See Also

fixVis for precise manipulation of plots.

### Examples

    # Load the test data
    data(immdata)

    # Compute and visualise:
    ov <- repOverlap(immdata$data)
    vis(ov)

    gu <- geneUsage(immdata$data)
    vis(gu)

    dv <- repDiversity(immdata$data)
    vis(dv)

[Package immunarch version 0.6.7 Index]