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[Deprecated]

Visualise distributions of genes using heatmaps or other plots.

Usage

# S3 method for class 'immunr_gene_usage'
vis(.data, .plot = c("hist", "box", "heatmap", "heatmap2", "circos"), ...)

Arguments

.data

Output from the geneUsage function.

.plot

String specifying the plot type:

...

Other arguments passed to corresponding functions depending on the plot type:

Value

A ggplot2 object, pheatmap or circlize object.

See also

Examples

# \dontrun{
data(immdata)

gu <- geneUsage(immdata$data[[1]])
vis(gu)
#> Using Names as id variables


gu <- geneUsage(immdata$data)
vis(gu, .by = "Status", .meta = immdata$meta)
#> Using Names as id variables
#> Warning: Removed 15 rows containing non-finite outside the scale range
#> (`stat_compare_means()`).
#> Warning: Removed 15 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_text()`).

vis(gu, "box", .by = "Status", .meta = immdata$meta)
#> Using Names as id variables
#> Warning: Removed 15 rows containing non-finite outside the scale range
#> (`stat_boxplot()`).
#> Warning: Removed 15 rows containing non-finite outside the scale range
#> (`stat_compare_means()`).
#> Warning: Removed 15 rows containing missing values or values outside the scale range
#> (`geom_point()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_text()`).

# }