Visualisation of distributions using ggplot2-based boxplots.
vis_box(
.data,
.by = NA,
.meta = NA,
.melt = TRUE,
.points = TRUE,
.test = TRUE,
.signif.label.size = 3.5,
.defgroupby = "Sample",
.grouping.var = "Group",
.labs = c("X", "Y"),
.title = "Boxplot (.title argument)",
.subtitle = "Subtitle (.subtitle argument)",
.legend = NA,
.leg.title = "Legend (.leg.title argument)",
.legend.pos = "right"
)
A ggplot2 object.
Input matrix or data frame.
Pass NA if you want to plot samples without grouping.
You can pass a character vector with one or several column names from ".meta" to group your data before plotting. In this case you should provide ".meta".
You can pass a character vector that exactly matches the number of samples in your data, each value should correspond to a sample's property. It will be used to group data based on the values provided. Note that in this case you should pass NA to ".meta".
A metadata object. An R dataframe with sample names and their properties, such as age, serostatus or hla.
If TRUE then apply reshape2::melt to the ".data" before plotting. In this case ".data" is supposed to be a data frame with the first character column reserved for names of genes and other numeric columns reserved to counts or frequencies of genes. Each numeric column should be associated with a specific repertoire sample.
A logical value defining whether points will be visualised or not.
A logical vector whether statistical tests should be applied. See "Details" for more information.
An integer value defining the size of text for p-value.
A name for the column with sample names.
A name for the column to group by.
Character vector of length two with names for x-axis and y-axis, respectively.
The text for the title of the plot.
The The text for the plot's subtitle.
If TRUE then displays a legend, otherwise removes legend from the plot.
The The text for the plots's legend. Provide NULL to remove the legend's title completely.
Positions of the legend: either "top", "bottom", "left" or "right".
vis.immunr_gene_usage, geneUsage
if (FALSE) {
vis_box(data.frame(Sample = sample(c("A", "B", "C"), 100, TRUE), Value = rnorm(100)), .melt = FALSE)
}
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